Overview

Dataset statistics

Number of variables71
Number of observations269
Missing cells0
Missing cells (%)0.0%
Duplicate rows61
Duplicate rows (%)22.7%
Total size in memory149.3 KiB
Average record size in memory568.5 B

Variable types

Categorical70
Numeric1

Alerts

Dataset has 61 (22.7%) duplicate rowsDuplicates
8 Which device do you use to access the online shopping? is highly correlated with 9 What is the screen size of your mobile device? and 5 other fieldsHigh correlation
9 What is the screen size of your mobile device? is highly correlated with 8 Which device do you use to access the online shopping? and 4 other fieldsHigh correlation
10 What is the operating system (OS) of your device? is highly correlated with 8 Which device do you use to access the online shopping? and 5 other fieldsHigh correlation
11 What browser do you run on your device to access the website? is highly correlated with 10 What is the operating system (OS) of your device? and 4 other fieldsHigh correlation
12 Which channel did you follow to arrive at your favorite online store for the first time? is highly correlated with 11 What browser do you run on your device to access the website? and 2 other fieldsHigh correlation
13 After first visit, how do you reach the online retail store? is highly correlated with 18 The content on the website must be easy to read and understand and 10 other fieldsHigh correlation
14 How much time do you explore the e- retail store before making a purchase decision? is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 1 other fieldsHigh correlation
16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? is highly correlated with 44 Shopping on your preferred e-tailer enhances your social statusHigh correlation
17 Why did you abandon the “Bag”, “Shopping Cart”? is highly correlated with 30 Online shopping gives monetary benefit and discountsHigh correlation
18 The content on the website must be easy to read and understand is highly correlated with 13 After first visit, how do you reach the online retail store? and 6 other fieldsHigh correlation
19 Information on similar product to the one highlighted is important for product comparison is highly correlated with 14 How much time do you explore the e- retail store before making a purchase decision? and 8 other fieldsHigh correlation
20 Complete information on listed seller and product being offered is important for purchase decision. is highly correlated with 13 After first visit, how do you reach the online retail store? and 4 other fieldsHigh correlation
21 All relevant information on listed products must be stated clearly is highly correlated with 18 The content on the website must be easy to read and understand and 6 other fieldsHigh correlation
22 Ease of navigation in website is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 5 other fieldsHigh correlation
23 Loading and processing speed is highly correlated with 18 The content on the website must be easy to read and understand and 8 other fieldsHigh correlation
24 User friendly Interface of the website is highly correlated with 8 Which device do you use to access the online shopping? and 12 other fieldsHigh correlation
25 Convenient Payment methods is highly correlated with 8 Which device do you use to access the online shopping? and 8 other fieldsHigh correlation
26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time is highly correlated with 18 The content on the website must be easy to read and understand and 8 other fieldsHigh correlation
27 Empathy (readiness to assist with queries) towards the customers is highly correlated with 22 Ease of navigation in website and 5 other fieldsHigh correlation
28 Being able to guarantee the privacy of the customer is highly correlated with 12 Which channel did you follow to arrive at your favorite online store for the first time? and 6 other fieldsHigh correlation
29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.) is highly correlated with 13 After first visit, how do you reach the online retail store? and 3 other fieldsHigh correlation
30 Online shopping gives monetary benefit and discounts is highly correlated with 8 Which device do you use to access the online shopping? and 10 other fieldsHigh correlation
31 Enjoyment is derived from shopping online is highly correlated with 8 Which device do you use to access the online shopping? and 9 other fieldsHigh correlation
32 Shopping online is convenient and flexible is highly correlated with 13 After first visit, how do you reach the online retail store? and 8 other fieldsHigh correlation
33 Return and replacement policy of the e-tailer is important for purchase decision is highly correlated with 11 What browser do you run on your device to access the website? and 5 other fieldsHigh correlation
34 Gaining access to loyalty programs is a benefit of shopping online is highly correlated with 11 What browser do you run on your device to access the website? and 5 other fieldsHigh correlation
35 Displaying quality Information on the website improves satisfaction of customers is highly correlated with 11 What browser do you run on your device to access the website? and 8 other fieldsHigh correlation
36 User derive satisfaction while shopping on a good quality website or application is highly correlated with 13 After first visit, how do you reach the online retail store? and 6 other fieldsHigh correlation
37 Net Benefit derived from shopping online can lead to users satisfaction is highly correlated with 13 After first visit, how do you reach the online retail store? and 12 other fieldsHigh correlation
38 User satisfaction cannot exist without trust is highly correlated with 18 The content on the website must be easy to read and understand and 3 other fieldsHigh correlation
39 Offering a wide variety of listed product in several category is highly correlated with 32 Shopping online is convenient and flexible and 3 other fieldsHigh correlation
40 Provision of complete and relevant product information is highly correlated with 12 Which channel did you follow to arrive at your favorite online store for the first time? and 6 other fieldsHigh correlation
41 Monetary savings is highly correlated with 10 What is the operating system (OS) of your device? and 2 other fieldsHigh correlation
42 The Convenience of patronizing the online retailer is highly correlated with 39 Offering a wide variety of listed product in several category and 1 other fieldsHigh correlation
43 Shopping on the website gives you the sense of adventure is highly correlated with 14 How much time do you explore the e- retail store before making a purchase decision? and 1 other fieldsHigh correlation
44 Shopping on your preferred e-tailer enhances your social status is highly correlated with 16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? High correlation
45 You feel gratification shopping on your favorite e-tailer is highly correlated with 47 Getting value for money spentHigh correlation
47 Getting value for money spent is highly correlated with 36 User derive satisfaction while shopping on a good quality website or application and 1 other fieldsHigh correlation
8 Which device do you use to access the online shopping? is highly correlated with 9 What is the screen size of your mobile device? and 5 other fieldsHigh correlation
9 What is the screen size of your mobile device? is highly correlated with 8 Which device do you use to access the online shopping? and 3 other fieldsHigh correlation
10 What is the operating system (OS) of your device? is highly correlated with 8 Which device do you use to access the online shopping? and 3 other fieldsHigh correlation
11 What browser do you run on your device to access the website? is highly correlated with 12 Which channel did you follow to arrive at your favorite online store for the first time? and 4 other fieldsHigh correlation
12 Which channel did you follow to arrive at your favorite online store for the first time? is highly correlated with 11 What browser do you run on your device to access the website? and 1 other fieldsHigh correlation
13 After first visit, how do you reach the online retail store? is highly correlated with 20 Complete information on listed seller and product being offered is important for purchase decision. and 6 other fieldsHigh correlation
14 How much time do you explore the e- retail store before making a purchase decision? is highly correlated with 43 Shopping on the website gives you the sense of adventureHigh correlation
16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? is highly correlated with 35 Displaying quality Information on the website improves satisfaction of customers and 1 other fieldsHigh correlation
17 Why did you abandon the “Bag”, “Shopping Cart”? is highly correlated with 30 Online shopping gives monetary benefit and discountsHigh correlation
18 The content on the website must be easy to read and understand is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 11 other fieldsHigh correlation
19 Information on similar product to the one highlighted is important for product comparison is highly correlated with 18 The content on the website must be easy to read and understand and 10 other fieldsHigh correlation
20 Complete information on listed seller and product being offered is important for purchase decision. is highly correlated with 13 After first visit, how do you reach the online retail store? and 3 other fieldsHigh correlation
21 All relevant information on listed products must be stated clearly is highly correlated with 18 The content on the website must be easy to read and understand and 9 other fieldsHigh correlation
22 Ease of navigation in website is highly correlated with 18 The content on the website must be easy to read and understand and 12 other fieldsHigh correlation
23 Loading and processing speed is highly correlated with 18 The content on the website must be easy to read and understand and 11 other fieldsHigh correlation
24 User friendly Interface of the website is highly correlated with 8 Which device do you use to access the online shopping? and 12 other fieldsHigh correlation
25 Convenient Payment methods is highly correlated with 8 Which device do you use to access the online shopping? and 13 other fieldsHigh correlation
26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time is highly correlated with 18 The content on the website must be easy to read and understand and 12 other fieldsHigh correlation
27 Empathy (readiness to assist with queries) towards the customers is highly correlated with 18 The content on the website must be easy to read and understand and 11 other fieldsHigh correlation
28 Being able to guarantee the privacy of the customer is highly correlated with 18 The content on the website must be easy to read and understand and 11 other fieldsHigh correlation
30 Online shopping gives monetary benefit and discounts is highly correlated with 8 Which device do you use to access the online shopping? and 13 other fieldsHigh correlation
31 Enjoyment is derived from shopping online is highly correlated with 8 Which device do you use to access the online shopping? and 10 other fieldsHigh correlation
32 Shopping online is convenient and flexible is highly correlated with 13 After first visit, how do you reach the online retail store? and 6 other fieldsHigh correlation
33 Return and replacement policy of the e-tailer is important for purchase decision is highly correlated with 11 What browser do you run on your device to access the website? and 6 other fieldsHigh correlation
34 Gaining access to loyalty programs is a benefit of shopping online is highly correlated with 35 Displaying quality Information on the website improves satisfaction of customers and 2 other fieldsHigh correlation
35 Displaying quality Information on the website improves satisfaction of customers is highly correlated with 11 What browser do you run on your device to access the website? and 9 other fieldsHigh correlation
36 User derive satisfaction while shopping on a good quality website or application is highly correlated with 11 What browser do you run on your device to access the website? and 6 other fieldsHigh correlation
37 Net Benefit derived from shopping online can lead to users satisfaction is highly correlated with 13 After first visit, how do you reach the online retail store? and 4 other fieldsHigh correlation
38 User satisfaction cannot exist without trust is highly correlated with 18 The content on the website must be easy to read and understand and 10 other fieldsHigh correlation
39 Offering a wide variety of listed product in several category is highly correlated with 34 Gaining access to loyalty programs is a benefit of shopping online and 1 other fieldsHigh correlation
40 Provision of complete and relevant product information is highly correlated with 11 What browser do you run on your device to access the website? and 5 other fieldsHigh correlation
41 Monetary savings is highly correlated with 32 Shopping online is convenient and flexible and 1 other fieldsHigh correlation
42 The Convenience of patronizing the online retailer is highly correlated with 43 Shopping on the website gives you the sense of adventureHigh correlation
43 Shopping on the website gives you the sense of adventure is highly correlated with 14 How much time do you explore the e- retail store before making a purchase decision? and 1 other fieldsHigh correlation
44 Shopping on your preferred e-tailer enhances your social status is highly correlated with 16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? and 4 other fieldsHigh correlation
45 You feel gratification shopping on your favorite e-tailer is highly correlated with 22 Ease of navigation in website and 3 other fieldsHigh correlation
46 Shopping on the website helps you fulfill certain roles is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 1 other fieldsHigh correlation
47 Getting value for money spent is highly correlated with 36 User derive satisfaction while shopping on a good quality website or applicationHigh correlation
8 Which device do you use to access the online shopping? is highly correlated with 9 What is the screen size of your mobile device? and 4 other fieldsHigh correlation
9 What is the screen size of your mobile device? is highly correlated with 8 Which device do you use to access the online shopping? and 2 other fieldsHigh correlation
10 What is the operating system (OS) of your device? is highly correlated with 8 Which device do you use to access the online shopping? and 3 other fieldsHigh correlation
11 What browser do you run on your device to access the website? is highly correlated with 10 What is the operating system (OS) of your device? and 3 other fieldsHigh correlation
12 Which channel did you follow to arrive at your favorite online store for the first time? is highly correlated with 11 What browser do you run on your device to access the website? and 1 other fieldsHigh correlation
13 After first visit, how do you reach the online retail store? is highly correlated with 30 Online shopping gives monetary benefit and discounts and 5 other fieldsHigh correlation
14 How much time do you explore the e- retail store before making a purchase decision? is highly correlated with 43 Shopping on the website gives you the sense of adventureHigh correlation
16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? is highly correlated with 44 Shopping on your preferred e-tailer enhances your social statusHigh correlation
18 The content on the website must be easy to read and understand is highly correlated with 21 All relevant information on listed products must be stated clearly and 4 other fieldsHigh correlation
19 Information on similar product to the one highlighted is important for product comparison is highly correlated with 21 All relevant information on listed products must be stated clearly and 5 other fieldsHigh correlation
20 Complete information on listed seller and product being offered is important for purchase decision. is highly correlated with 26 Trust that the online retail store will fulfill its part of the transaction at the stipulated timeHigh correlation
21 All relevant information on listed products must be stated clearly is highly correlated with 18 The content on the website must be easy to read and understand and 6 other fieldsHigh correlation
22 Ease of navigation in website is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 5 other fieldsHigh correlation
23 Loading and processing speed is highly correlated with 18 The content on the website must be easy to read and understand and 7 other fieldsHigh correlation
24 User friendly Interface of the website is highly correlated with 18 The content on the website must be easy to read and understand and 9 other fieldsHigh correlation
25 Convenient Payment methods is highly correlated with 8 Which device do you use to access the online shopping? and 5 other fieldsHigh correlation
26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 6 other fieldsHigh correlation
27 Empathy (readiness to assist with queries) towards the customers is highly correlated with 22 Ease of navigation in website and 4 other fieldsHigh correlation
28 Being able to guarantee the privacy of the customer is highly correlated with 19 Information on similar product to the one highlighted is important for product comparison and 5 other fieldsHigh correlation
29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.) is highly correlated with 32 Shopping online is convenient and flexible and 1 other fieldsHigh correlation
30 Online shopping gives monetary benefit and discounts is highly correlated with 8 Which device do you use to access the online shopping? and 4 other fieldsHigh correlation
31 Enjoyment is derived from shopping online is highly correlated with 8 Which device do you use to access the online shopping? and 6 other fieldsHigh correlation
32 Shopping online is convenient and flexible is highly correlated with 13 After first visit, how do you reach the online retail store? and 6 other fieldsHigh correlation
33 Return and replacement policy of the e-tailer is important for purchase decision is highly correlated with 13 After first visit, how do you reach the online retail store? and 2 other fieldsHigh correlation
34 Gaining access to loyalty programs is a benefit of shopping online is highly correlated with 11 What browser do you run on your device to access the website? and 2 other fieldsHigh correlation
35 Displaying quality Information on the website improves satisfaction of customers is highly correlated with 11 What browser do you run on your device to access the website? and 6 other fieldsHigh correlation
36 User derive satisfaction while shopping on a good quality website or application is highly correlated with 13 After first visit, how do you reach the online retail store? and 4 other fieldsHigh correlation
37 Net Benefit derived from shopping online can lead to users satisfaction is highly correlated with 13 After first visit, how do you reach the online retail store? and 7 other fieldsHigh correlation
38 User satisfaction cannot exist without trust is highly correlated with 18 The content on the website must be easy to read and understand and 3 other fieldsHigh correlation
39 Offering a wide variety of listed product in several category is highly correlated with 34 Gaining access to loyalty programs is a benefit of shopping online and 1 other fieldsHigh correlation
40 Provision of complete and relevant product information is highly correlated with 12 Which channel did you follow to arrive at your favorite online store for the first time? and 4 other fieldsHigh correlation
41 Monetary savings is highly correlated with 29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.)High correlation
42 The Convenience of patronizing the online retailer is highly correlated with 43 Shopping on the website gives you the sense of adventureHigh correlation
43 Shopping on the website gives you the sense of adventure is highly correlated with 14 How much time do you explore the e- retail store before making a purchase decision? and 1 other fieldsHigh correlation
44 Shopping on your preferred e-tailer enhances your social status is highly correlated with 16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? High correlation
43 Shopping on the website gives you the sense of adventure is highly correlated with 24 User friendly Interface of the website and 30 other fieldsHigh correlation
24 User friendly Interface of the website is highly correlated with 43 Shopping on the website gives you the sense of adventure and 39 other fieldsHigh correlation
Longer delivery period is highly correlated with 43 Shopping on the website gives you the sense of adventure and 41 other fieldsHigh correlation
11 What browser do you run on your device to access the website? is highly correlated with 43 Shopping on the website gives you the sense of adventure and 23 other fieldsHigh correlation
Longer time to get logged in (promotion, sales period) is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
Longer page loading time (promotion, sales period) is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
10 What is the operating system (OS) of your device? is highly correlated with Longer delivery period and 29 other fieldsHigh correlation
9 What is the screen size of your mobile device? is highly correlated with 43 Shopping on the website gives you the sense of adventure and 28 other fieldsHigh correlation
23 Loading and processing speed is highly correlated with 24 User friendly Interface of the website and 41 other fieldsHigh correlation
Complete, relevant description information of products is highly correlated with 43 Shopping on the website gives you the sense of adventure and 54 other fieldsHigh correlation
Longer time in displaying graphics and photos (promotion, sales period) is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
Website is as efficient as before is highly correlated with 43 Shopping on the website gives you the sense of adventure and 56 other fieldsHigh correlation
45 You feel gratification shopping on your favorite e-tailer is highly correlated with 24 User friendly Interface of the website and 44 other fieldsHigh correlation
1Gender of respondent is highly correlated with 3 Which city do you shop online from?High correlation
33 Return and replacement policy of the e-tailer is important for purchase decision is highly correlated with 24 User friendly Interface of the website and 30 other fieldsHigh correlation
39 Offering a wide variety of listed product in several category is highly correlated with Longer delivery period and 28 other fieldsHigh correlation
17 Why did you abandon the “Bag”, “Shopping Cart”? is highly correlated with Longer delivery period and 32 other fieldsHigh correlation
37 Net Benefit derived from shopping online can lead to users satisfaction is highly correlated with 24 User friendly Interface of the website and 34 other fieldsHigh correlation
19 Information on similar product to the one highlighted is important for product comparison is highly correlated with 24 User friendly Interface of the website and 41 other fieldsHigh correlation
20 Complete information on listed seller and product being offered is important for purchase decision. is highly correlated with 24 User friendly Interface of the website and 42 other fieldsHigh correlation
34 Gaining access to loyalty programs is a benefit of shopping online is highly correlated with Longer time to get logged in (promotion, sales period) and 29 other fieldsHigh correlation
Speedy order delivery is highly correlated with Longer delivery period and 39 other fieldsHigh correlation
Quickness to complete purchase is highly correlated with 43 Shopping on the website gives you the sense of adventure and 57 other fieldsHigh correlation
Security of customer financial information is highly correlated with 43 Shopping on the website gives you the sense of adventure and 62 other fieldsHigh correlation
18 The content on the website must be easy to read and understand is highly correlated with 24 User friendly Interface of the website and 35 other fieldsHigh correlation
12 Which channel did you follow to arrive at your favorite online store for the first time? is highly correlated with 24 User friendly Interface of the website and 19 other fieldsHigh correlation
25 Convenient Payment methods is highly correlated with 24 User friendly Interface of the website and 36 other fieldsHigh correlation
26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time is highly correlated with 43 Shopping on the website gives you the sense of adventure and 37 other fieldsHigh correlation
32 Shopping online is convenient and flexible is highly correlated with 24 User friendly Interface of the website and 33 other fieldsHigh correlation
21 All relevant information on listed products must be stated clearly is highly correlated with 43 Shopping on the website gives you the sense of adventure and 36 other fieldsHigh correlation
Easy to use website or application is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
Reliability of the website or application is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
Availability of several payment options is highly correlated with 43 Shopping on the website gives you the sense of adventure and 60 other fieldsHigh correlation
Late declaration of price (promotion, sales period) is highly correlated with 43 Shopping on the website gives you the sense of adventure and 48 other fieldsHigh correlation
Change in website/Application design is highly correlated with 24 User friendly Interface of the website and 39 other fieldsHigh correlation
41 Monetary savings is highly correlated with 24 User friendly Interface of the website and 30 other fieldsHigh correlation
36 User derive satisfaction while shopping on a good quality website or application is highly correlated with 11 What browser do you run on your device to access the website? and 22 other fieldsHigh correlation
44 Shopping on your preferred e-tailer enhances your social status is highly correlated with Longer delivery period and 30 other fieldsHigh correlation
Fast loading website speed of website and application is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
35 Displaying quality Information on the website improves satisfaction of customers is highly correlated with Longer time to get logged in (promotion, sales period) and 33 other fieldsHigh correlation
Privacy of customers’ information is highly correlated with 43 Shopping on the website gives you the sense of adventure and 61 other fieldsHigh correlation
28 Being able to guarantee the privacy of the customer is highly correlated with 24 User friendly Interface of the website and 34 other fieldsHigh correlation
8 Which device do you use to access the online shopping? is highly correlated with 24 User friendly Interface of the website and 33 other fieldsHigh correlation
Which of the Indian online retailer would you recommend to a friend? is highly correlated with 43 Shopping on the website gives you the sense of adventure and 42 other fieldsHigh correlation
13 After first visit, how do you reach the online retail store? is highly correlated with 24 User friendly Interface of the website and 42 other fieldsHigh correlation
42 The Convenience of patronizing the online retailer is highly correlated with 43 Shopping on the website gives you the sense of adventure and 31 other fieldsHigh correlation
From the following, tick any (or all) of the online retailers you have shopped from; is highly correlated with 43 Shopping on the website gives you the sense of adventure and 60 other fieldsHigh correlation
Limited mode of payment on most products (promotion, sales period) is highly correlated with 43 Shopping on the website gives you the sense of adventure and 58 other fieldsHigh correlation
3 Which city do you shop online from? is highly correlated with 1Gender of respondent and 1 other fieldsHigh correlation
22 Ease of navigation in website is highly correlated with 43 Shopping on the website gives you the sense of adventure and 30 other fieldsHigh correlation
40 Provision of complete and relevant product information is highly correlated with 43 Shopping on the website gives you the sense of adventure and 30 other fieldsHigh correlation
Presence of online assistance through multi-channel is highly correlated with 43 Shopping on the website gives you the sense of adventure and 56 other fieldsHigh correlation
Visual appealing web-page layout is highly correlated with 43 Shopping on the website gives you the sense of adventure and 59 other fieldsHigh correlation
46 Shopping on the website helps you fulfill certain roles is highly correlated with Longer delivery period and 37 other fieldsHigh correlation
14 How much time do you explore the e- retail store before making a purchase decision? is highly correlated with Longer time to get logged in (promotion, sales period) and 24 other fieldsHigh correlation
16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? is highly correlated with Longer time to get logged in (promotion, sales period) and 23 other fieldsHigh correlation
30 Online shopping gives monetary benefit and discounts is highly correlated with 24 User friendly Interface of the website and 49 other fieldsHigh correlation
38 User satisfaction cannot exist without trust is highly correlated with 43 Shopping on the website gives you the sense of adventure and 36 other fieldsHigh correlation
Perceived Trustworthiness is highly correlated with 43 Shopping on the website gives you the sense of adventure and 55 other fieldsHigh correlation
47 Getting value for money spent is highly correlated with Longer time to get logged in (promotion, sales period) and 25 other fieldsHigh correlation
Wild variety of product on offer is highly correlated with 43 Shopping on the website gives you the sense of adventure and 52 other fieldsHigh correlation
15 What is your preferred payment Option? is highly correlated with Longer delivery period and 24 other fieldsHigh correlation
27 Empathy (readiness to assist with queries) towards the customers is highly correlated with 24 User friendly Interface of the website and 28 other fieldsHigh correlation
Frequent disruption when moving from one page to another is highly correlated with 43 Shopping on the website gives you the sense of adventure and 54 other fieldsHigh correlation
31 Enjoyment is derived from shopping online is highly correlated with 24 User friendly Interface of the website and 47 other fieldsHigh correlation
29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.) is highly correlated with Longer delivery period and 26 other fieldsHigh correlation
1Gender of respondent is highly correlated with 3 Which city do you shop online from? and 5 other fieldsHigh correlation
2 How old are you? is highly correlated with 3 Which city do you shop online from? and 25 other fieldsHigh correlation
3 Which city do you shop online from? is highly correlated with 1Gender of respondent and 59 other fieldsHigh correlation
4 What is the Pin Code of where you shop online from? is highly correlated with 2 How old are you? and 28 other fieldsHigh correlation
5 Since How Long You are Shopping Online ? is highly correlated with 3 Which city do you shop online from? and 16 other fieldsHigh correlation
6 How many times you have made an online purchase in the past 1 year? is highly correlated with 3 Which city do you shop online from? and 21 other fieldsHigh correlation
7 How do you access the internet while shopping on-line? is highly correlated with 8 Which device do you use to access the online shopping? and 11 other fieldsHigh correlation
8 Which device do you use to access the online shopping? is highly correlated with 7 How do you access the internet while shopping on-line? and 51 other fieldsHigh correlation
9 What is the screen size of your mobile device? is highly correlated with 8 Which device do you use to access the online shopping? and 41 other fieldsHigh correlation
10 What is the operating system (OS) of your device? is highly correlated with 8 Which device do you use to access the online shopping? and 43 other fieldsHigh correlation
11 What browser do you run on your device to access the website? is highly correlated with 3 Which city do you shop online from? and 48 other fieldsHigh correlation
12 Which channel did you follow to arrive at your favorite online store for the first time? is highly correlated with 3 Which city do you shop online from? and 37 other fieldsHigh correlation
13 After first visit, how do you reach the online retail store? is highly correlated with 3 Which city do you shop online from? and 55 other fieldsHigh correlation
14 How much time do you explore the e- retail store before making a purchase decision? is highly correlated with 2 How old are you? and 51 other fieldsHigh correlation
15 What is your preferred payment Option? is highly correlated with 3 Which city do you shop online from? and 36 other fieldsHigh correlation
16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart? is highly correlated with 8 Which device do you use to access the online shopping? and 42 other fieldsHigh correlation
17 Why did you abandon the “Bag”, “Shopping Cart”? is highly correlated with 2 How old are you? and 54 other fieldsHigh correlation
18 The content on the website must be easy to read and understand is highly correlated with 3 Which city do you shop online from? and 54 other fieldsHigh correlation
19 Information on similar product to the one highlighted is important for product comparison is highly correlated with 3 Which city do you shop online from? and 56 other fieldsHigh correlation
20 Complete information on listed seller and product being offered is important for purchase decision. is highly correlated with 2 How old are you? and 56 other fieldsHigh correlation
21 All relevant information on listed products must be stated clearly is highly correlated with 3 Which city do you shop online from? and 53 other fieldsHigh correlation
22 Ease of navigation in website is highly correlated with 3 Which city do you shop online from? and 49 other fieldsHigh correlation
23 Loading and processing speed is highly correlated with 2 How old are you? and 58 other fieldsHigh correlation
24 User friendly Interface of the website is highly correlated with 3 Which city do you shop online from? and 55 other fieldsHigh correlation
25 Convenient Payment methods is highly correlated with 3 Which city do you shop online from? and 55 other fieldsHigh correlation
26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time is highly correlated with 3 Which city do you shop online from? and 53 other fieldsHigh correlation
27 Empathy (readiness to assist with queries) towards the customers is highly correlated with 8 Which device do you use to access the online shopping? and 48 other fieldsHigh correlation
28 Being able to guarantee the privacy of the customer is highly correlated with 8 Which device do you use to access the online shopping? and 52 other fieldsHigh correlation
29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.) is highly correlated with 1Gender of respondent and 48 other fieldsHigh correlation
30 Online shopping gives monetary benefit and discounts is highly correlated with 2 How old are you? and 61 other fieldsHigh correlation
31 Enjoyment is derived from shopping online is highly correlated with 2 How old are you? and 61 other fieldsHigh correlation
32 Shopping online is convenient and flexible is highly correlated with 7 How do you access the internet while shopping on-line? and 50 other fieldsHigh correlation
33 Return and replacement policy of the e-tailer is important for purchase decision is highly correlated with 9 What is the screen size of your mobile device? and 46 other fieldsHigh correlation
34 Gaining access to loyalty programs is a benefit of shopping online is highly correlated with 3 Which city do you shop online from? and 55 other fieldsHigh correlation
35 Displaying quality Information on the website improves satisfaction of customers is highly correlated with 3 Which city do you shop online from? and 45 other fieldsHigh correlation
36 User derive satisfaction while shopping on a good quality website or application is highly correlated with 9 What is the screen size of your mobile device? and 41 other fieldsHigh correlation
37 Net Benefit derived from shopping online can lead to users satisfaction is highly correlated with 1Gender of respondent and 55 other fieldsHigh correlation
38 User satisfaction cannot exist without trust is highly correlated with 2 How old are you? and 55 other fieldsHigh correlation
39 Offering a wide variety of listed product in several category is highly correlated with 3 Which city do you shop online from? and 48 other fieldsHigh correlation
40 Provision of complete and relevant product information is highly correlated with 1Gender of respondent and 48 other fieldsHigh correlation
41 Monetary savings is highly correlated with 3 Which city do you shop online from? and 49 other fieldsHigh correlation
42 The Convenience of patronizing the online retailer is highly correlated with 3 Which city do you shop online from? and 45 other fieldsHigh correlation
43 Shopping on the website gives you the sense of adventure is highly correlated with 3 Which city do you shop online from? and 52 other fieldsHigh correlation
44 Shopping on your preferred e-tailer enhances your social status is highly correlated with 3 Which city do you shop online from? and 55 other fieldsHigh correlation
45 You feel gratification shopping on your favorite e-tailer is highly correlated with 2 How old are you? and 57 other fieldsHigh correlation
46 Shopping on the website helps you fulfill certain roles is highly correlated with 2 How old are you? and 53 other fieldsHigh correlation
47 Getting value for money spent is highly correlated with 3 Which city do you shop online from? and 45 other fieldsHigh correlation
From the following, tick any (or all) of the online retailers you have shopped from; is highly correlated with 2 How old are you? and 65 other fieldsHigh correlation
Easy to use website or application is highly correlated with 1Gender of respondent and 69 other fieldsHigh correlation
Visual appealing web-page layout is highly correlated with 1Gender of respondent and 69 other fieldsHigh correlation
Wild variety of product on offer is highly correlated with 2 How old are you? and 66 other fieldsHigh correlation
Complete, relevant description information of products is highly correlated with 2 How old are you? and 68 other fieldsHigh correlation
Fast loading website speed of website and application is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Reliability of the website or application is highly correlated with 2 How old are you? and 68 other fieldsHigh correlation
Quickness to complete purchase is highly correlated with 2 How old are you? and 65 other fieldsHigh correlation
Availability of several payment options is highly correlated with 2 How old are you? and 68 other fieldsHigh correlation
Speedy order delivery is highly correlated with 3 Which city do you shop online from? and 60 other fieldsHigh correlation
Privacy of customers’ information is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Security of customer financial information is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Perceived Trustworthiness is highly correlated with 3 Which city do you shop online from? and 64 other fieldsHigh correlation
Presence of online assistance through multi-channel is highly correlated with 2 How old are you? and 68 other fieldsHigh correlation
Longer time to get logged in (promotion, sales period) is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Longer time in displaying graphics and photos (promotion, sales period) is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Late declaration of price (promotion, sales period) is highly correlated with 3 Which city do you shop online from? and 64 other fieldsHigh correlation
Longer page loading time (promotion, sales period) is highly correlated with 2 How old are you? and 67 other fieldsHigh correlation
Limited mode of payment on most products (promotion, sales period) is highly correlated with 3 Which city do you shop online from? and 62 other fieldsHigh correlation
Longer delivery period is highly correlated with 3 Which city do you shop online from? and 62 other fieldsHigh correlation
Change in website/Application design is highly correlated with 3 Which city do you shop online from? and 61 other fieldsHigh correlation
Frequent disruption when moving from one page to another is highly correlated with 3 Which city do you shop online from? and 65 other fieldsHigh correlation
Website is as efficient as before is highly correlated with 3 Which city do you shop online from? and 63 other fieldsHigh correlation
Which of the Indian online retailer would you recommend to a friend? is highly correlated with 3 Which city do you shop online from? and 63 other fieldsHigh correlation

Reproduction

Analysis started2022-06-09 16:08:42.527498
Analysis finished2022-06-09 16:09:02.580983
Duration20.05 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

1Gender of respondent
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
180 
0
89 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1180
66.9%
089
33.1%

Length

2022-06-09T21:39:02.670742image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:02.767483image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1180
66.9%
089
33.1%

Most occurring characters

ValueCountFrequency (%)
1180
66.9%
089
33.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1180
66.9%
089
33.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1180
66.9%
089
33.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1180
66.9%
089
33.1%

2 How old are you?
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
81 
2
79 
4
70 
1
20 
5
19 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

Length

2022-06-09T21:39:02.859238image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:02.960000image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

Most occurring characters

ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
381
30.1%
279
29.4%
470
26.0%
120
 
7.4%
519
 
7.1%

3 Which city do you shop online from?
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Delhi
58 
Greater Noida
43 
Noida
40 
Bangalore
37 
Karnal
27 
Other values (6)
64 

Length

Max length13
Median length11
Mean length7.721189591
Min length5

Characters and Unicode

Total characters2077
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDelhi
2nd rowDelhi
3rd rowGreater Noida
4th rowKarnal
5th rowBangalore

Common Values

ValueCountFrequency (%)
Delhi58
21.6%
Greater Noida43
16.0%
Noida40
14.9%
Bangalore 37
13.8%
Karnal 27
10.0%
Solan18
 
6.7%
Ghaziabad18
 
6.7%
Gurgaon 12
 
4.5%
Merrut9
 
3.3%
Moradabad5
 
1.9%

Length

2022-06-09T21:39:03.058706image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
noida83
26.6%
delhi58
18.6%
greater43
13.8%
bangalore37
11.9%
karnal27
 
8.7%
solan18
 
5.8%
ghaziabad18
 
5.8%
gurgaon12
 
3.8%
merrut9
 
2.9%
moradabad5
 
1.6%

Most occurring characters

ValueCountFrequency (%)
a357
17.2%
e190
 
9.1%
r187
 
9.0%
i159
 
7.7%
o155
 
7.5%
l142
 
6.8%
119
 
5.7%
d113
 
5.4%
n96
 
4.6%
N83
 
4.0%
Other values (13)476
22.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1646
79.2%
Uppercase Letter312
 
15.0%
Space Separator119
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a357
21.7%
e190
11.5%
r187
11.4%
i159
9.7%
o155
9.4%
l142
 
8.6%
d113
 
6.9%
n96
 
5.8%
h80
 
4.9%
t52
 
3.2%
Other values (5)115
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
N83
26.6%
G73
23.4%
D58
18.6%
B39
12.5%
K27
 
8.7%
S18
 
5.8%
M14
 
4.5%
Space Separator
ValueCountFrequency (%)
119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1958
94.3%
Common119
 
5.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a357
18.2%
e190
9.7%
r187
9.6%
i159
8.1%
o155
 
7.9%
l142
 
7.3%
d113
 
5.8%
n96
 
4.9%
N83
 
4.2%
h80
 
4.1%
Other values (12)396
20.2%
Common
ValueCountFrequency (%)
119
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a357
17.2%
e190
 
9.1%
r187
 
9.0%
i159
 
7.7%
o155
 
7.5%
l142
 
6.8%
119
 
5.7%
d113
 
5.4%
n96
 
4.6%
N83
 
4.0%
Other values (13)476
22.9%

4 What is the Pin Code of where you shop online from?
Real number (ℝ≥0)

HIGH CORRELATION

Distinct39
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220465.7472
Minimum110008
Maximum560037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2022-06-09T21:39:03.162458image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum110008
5-th percentile110011
Q1122018
median201303
Q3201310
95-th percentile560013
Maximum560037
Range450029
Interquartile range (IQR)79292

Descriptive statistics

Standard deviation140524.3411
Coefficient of variation (CV)0.6373976131
Kurtosis1.690834547
Mean220465.7472
Median Absolute Deviation (MAD)48698
Skewness1.748322464
Sum59305286
Variance1.974709043 × 1010
MonotonicityNot monotonic
2022-06-09T21:39:03.273172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
20130838
 
14.1%
13200119
 
7.1%
20131018
 
6.7%
11004416
 
5.9%
2500019
 
3.3%
1732299
 
3.3%
1732129
 
3.3%
5600108
 
3.0%
1320368
 
3.0%
1220188
 
3.0%
Other values (29)127
47.2%
ValueCountFrequency (%)
1100087
2.6%
1100094
 
1.5%
1100117
2.6%
1100146
 
2.2%
1100186
 
2.2%
1100304
 
1.5%
1100394
 
1.5%
1100424
 
1.5%
11004416
5.9%
1220094
 
1.5%
ValueCountFrequency (%)
5600378
3.0%
5600184
1.5%
5600133
 
1.1%
5600108
3.0%
5600034
1.5%
5600024
1.5%
5600011
 
0.4%
5300685
1.9%
2500019
3.3%
2440015
1.9%
Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
98 
3
65 
4
47 
1
43 
2
16 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row4
4th row4
5th row3

Common Values

ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%

Length

2022-06-09T21:39:03.360939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:03.562470image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%

Most occurring characters

ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
598
36.4%
365
24.2%
447
17.5%
143
16.0%
216
 
5.9%
Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
114 
4
63 
5
53 
2
29 
3
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%

Length

2022-06-09T21:39:03.641259image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:03.724038image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%

Most occurring characters

ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1114
42.4%
463
23.4%
553
19.7%
229
 
10.8%
310
 
3.7%
Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
118 
2
76 
5
71 
4
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

Length

2022-06-09T21:39:03.806786image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:03.887568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

Most occurring characters

ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3118
43.9%
276
28.3%
571
26.4%
44
 
1.5%

8 Which device do you use to access the online shopping?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
141 
2
86 
3
30 
4
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

Length

2022-06-09T21:39:03.969350image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.054154image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

Most occurring characters

ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1141
52.4%
286
32.0%
330
 
11.2%
412
 
4.5%

9 What is the screen size of your mobile device?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
134 
4
106 
2
29 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row2
3rd row4
4th row4
5th row2

Common Values

ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

Length

2022-06-09T21:39:04.127958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.204752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

Most occurring characters

ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5134
49.8%
4106
39.4%
229
 
10.8%

10 What is the operating system (OS) of your device?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
122 
2
85 
3
62 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row2
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

Length

2022-06-09T21:39:04.276559image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.354319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

Most occurring characters

ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1122
45.4%
285
31.6%
362
23.0%

11 What browser do you run on your device to access the website?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
216 
2
40 
4
 
8
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

Length

2022-06-09T21:39:04.426128image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.505915image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

Most occurring characters

ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1216
80.3%
240
 
14.9%
48
 
3.0%
35
 
1.9%

12 Which channel did you follow to arrive at your favorite online store for the first time?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
230 
3
 
20
4
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

Length

2022-06-09T21:39:04.577757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.653553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

Most occurring characters

ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1230
85.5%
320
 
7.4%
419
 
7.1%

13 After first visit, how do you reach the online retail store?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
95 
4
86 
3
70 
2
18 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row4
3rd row4
4th row1
5th row4

Common Values

ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

Length

2022-06-09T21:39:04.721439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.801195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

Most occurring characters

ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
195
35.3%
486
32.0%
370
26.0%
218
 
6.7%

14 How much time do you explore the e- retail store before making a purchase decision?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
123 
3
71 
4
46 
1
15 
2
14 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row4
4th row3
5th row5

Common Values

ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

Length

2022-06-09T21:39:04.879019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:04.961829image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

Most occurring characters

ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5123
45.7%
371
26.4%
446
 
17.1%
115
 
5.6%
214
 
5.2%

15 What is your preferred payment Option?
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
148 
2
76 
4
45 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row4
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

Length

2022-06-09T21:39:05.040588image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.123396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

Most occurring characters

ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1148
55.0%
276
28.3%
445
 
16.7%

16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
171 
1
48 
4
35 
5
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row3
4th row1
5th row4

Common Values

ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

Length

2022-06-09T21:39:05.195174image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.277033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

Most occurring characters

ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3171
63.6%
148
 
17.8%
435
 
13.0%
515
 
5.6%

17 Why did you abandon the “Bag”, “Shopping Cart”?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2
133 
5
54 
1
37 
3
31 
4
14 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

Length

2022-06-09T21:39:05.350799image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.433577image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

Most occurring characters

ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2133
49.4%
554
20.1%
137
 
13.8%
331
 
11.5%
414
 
5.2%

18 The content on the website must be easy to read and understand
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
164 
4
80 
1
18 
3
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

Length

2022-06-09T21:39:05.512397image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.591188image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

Most occurring characters

ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5164
61.0%
480
29.7%
118
 
6.7%
37
 
2.6%

19 Information on similar product to the one highlighted is important for product comparison
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
116 
4
92 
3
43 
2
18 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row4
4th row4
5th row3

Common Values

ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

Length

2022-06-09T21:39:05.661001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.739789image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

Most occurring characters

ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5116
43.1%
492
34.2%
343
 
16.0%
218
 
6.7%

20 Complete information on listed seller and product being offered is important for purchase decision.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
101 
5
87 
3
52 
2
18 
1
11 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row4
4th row3
5th row3

Common Values

ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

Length

2022-06-09T21:39:05.813591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:05.894377image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

Most occurring characters

ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4101
37.5%
587
32.3%
352
19.3%
218
 
6.7%
111
 
4.1%

21 All relevant information on listed products must be stated clearly
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
132 
5
107 
1
18 
2
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

Length

2022-06-09T21:39:05.972167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.061896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

Most occurring characters

ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4132
49.1%
5107
39.8%
118
 
6.7%
212
 
4.5%

22 Ease of navigation in website
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
141 
4
105 
1
18 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row4
4th row5
5th row4

Common Values

ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

Length

2022-06-09T21:39:06.135730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.215516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

Most occurring characters

ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5141
52.4%
4105
39.0%
118
 
6.7%
25
 
1.9%

23 Loading and processing speed
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
115 
4
112 
2
18 
1
12 
3
12 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row4
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

Length

2022-06-09T21:39:06.286327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.368181image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

Most occurring characters

ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5115
42.8%
4112
41.6%
218
 
6.7%
112
 
4.5%
312
 
4.5%

24 User friendly Interface of the website
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
189 
4
45 
1
 
18
2
 
12
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

Length

2022-06-09T21:39:06.443944image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.523730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

Most occurring characters

ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5189
70.3%
445
 
16.7%
118
 
6.7%
212
 
4.5%
35
 
1.9%

25 Convenient Payment methods
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
159 
4
80 
2
30 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

Length

2022-06-09T21:39:06.745169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.822962image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

Most occurring characters

ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5159
59.1%
480
29.7%
230
 
11.2%

26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
141 
4
86 
2
30 
3
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row4
5th row4

Common Values

ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

Length

2022-06-09T21:39:06.892777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:06.974560image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

Most occurring characters

ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5141
52.4%
486
32.0%
230
 
11.2%
312
 
4.5%

27 Empathy (readiness to assist with queries) towards the customers
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
194 
4
42 
1
 
18
3
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

Length

2022-06-09T21:39:07.047362image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.128184image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

Most occurring characters

ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5194
72.1%
442
 
15.6%
118
 
6.7%
315
 
5.6%

28 Being able to guarantee the privacy of the customer
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
185 
4
58 
3
26 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row5
5th row4

Common Values

ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

Length

2022-06-09T21:39:07.197000image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.271800image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

Most occurring characters

ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5185
68.8%
458
 
21.6%
326
 
9.7%

29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
149 
4
94 
3
15 
1
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

Length

2022-06-09T21:39:07.339618image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.413420image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

Most occurring characters

ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5149
55.4%
494
34.9%
315
 
5.6%
111
 
4.1%

30 Online shopping gives monetary benefit and discounts
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
105 
4
85 
3
50 
1
18 
2
11 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

Length

2022-06-09T21:39:07.481239image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.558034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

Most occurring characters

ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5105
39.0%
485
31.6%
350
18.6%
118
 
6.7%
211
 
4.1%

31 Enjoyment is derived from shopping online
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
86 
3
75 
4
59 
1
30 
2
19 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row5
4th row3
5th row5

Common Values

ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

Length

2022-06-09T21:39:07.631986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.711807image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

Most occurring characters

ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
586
32.0%
375
27.9%
459
21.9%
130
 
11.2%
219
 
7.1%

32 Shopping online is convenient and flexible
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
146 
4
78 
3
33 
2
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row3
5th row5

Common Values

ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

Length

2022-06-09T21:39:07.787602image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:07.864397image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

Most occurring characters

ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5146
54.3%
478
29.0%
333
 
12.3%
212
 
4.5%

33 Return and replacement policy of the e-tailer is important for purchase decision
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
198 
4
51 
2
20 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

Length

2022-06-09T21:39:07.935210image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.012040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

Most occurring characters

ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5198
73.6%
451
 
19.0%
220
 
7.4%

34 Gaining access to loyalty programs is a benefit of shopping online
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
115 
4
64 
3
64 
2
15 
1
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row3
5th row2

Common Values

ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

Length

2022-06-09T21:39:08.076867image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.155656image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

Most occurring characters

ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5115
42.8%
464
23.8%
364
23.8%
215
 
5.6%
111
 
4.1%

35 Displaying quality Information on the website improves satisfaction of customers
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
133 
4
80 
3
56 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row3
5th row4

Common Values

ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

Length

2022-06-09T21:39:08.231453image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.307252image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

Most occurring characters

ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5133
49.4%
480
29.7%
356
20.8%

36 User derive satisfaction while shopping on a good quality website or application
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
175 
4
86 
2
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

Length

2022-06-09T21:39:08.376068image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.451865image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

Most occurring characters

ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5175
65.1%
486
32.0%
28
 
3.0%

37 Net Benefit derived from shopping online can lead to users satisfaction
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
164 
4
54 
3
40 
2
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row5
4th row3
5th row5

Common Values

ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

Length

2022-06-09T21:39:08.519684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.597476image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

Most occurring characters

ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5164
61.0%
454
 
20.1%
340
 
14.9%
211
 
4.1%

38 User satisfaction cannot exist without trust
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
122 
4
117 
1
18 
2
 
7
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row4
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

Length

2022-06-09T21:39:08.674280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.756061image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

Most occurring characters

ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5122
45.4%
4117
43.5%
118
 
6.7%
27
 
2.6%
35
 
1.9%

39 Offering a wide variety of listed product in several category
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
111 
4
94 
3
57 
2
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row4
5th row4

Common Values

ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

Length

2022-06-09T21:39:08.828866image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:08.908652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

Most occurring characters

ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5111
41.3%
494
34.9%
357
21.2%
27
 
2.6%

40 Provision of complete and relevant product information
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
135 
4
98 
3
31 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row4
5th row4

Common Values

ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

Length

2022-06-09T21:39:08.980460image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.059248image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

Most occurring characters

ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5135
50.2%
498
36.4%
331
 
11.5%
25
 
1.9%

41 Monetary savings
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
5
148 
4
75 
2
31 
3
15 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

Length

2022-06-09T21:39:09.132053image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.209845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

Most occurring characters

ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5148
55.0%
475
27.9%
231
 
11.5%
315
 
5.6%

42 The Convenience of patronizing the online retailer
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
138 
3
77 
5
54 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

Length

2022-06-09T21:39:09.281653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.357450image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

Most occurring characters

ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4138
51.3%
377
28.6%
554
 
20.1%

43 Shopping on the website gives you the sense of adventure
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
101 
3
59 
5
54 
2
50 
1
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row4
4th row4
5th row3

Common Values

ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

Length

2022-06-09T21:39:09.426266image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.509045image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

Most occurring characters

ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4101
37.5%
359
21.9%
554
20.1%
250
18.6%
15
 
1.9%

44 Shopping on your preferred e-tailer enhances your social status
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
100 
4
59 
5
48 
1
33 
2
29 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row4
4th row5
5th row1

Common Values

ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

Length

2022-06-09T21:39:09.585839image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.669615image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

Most occurring characters

ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3100
37.2%
459
21.9%
548
17.8%
133
 
12.3%
229
 
10.8%

45 You feel gratification shopping on your favorite e-tailer
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
101 
5
65 
4
63 
2
22 
1
18 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row3
4th row4
5th row5

Common Values

ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

Length

2022-06-09T21:39:09.751396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.833177image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

Most occurring characters

ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3101
37.5%
565
24.2%
463
23.4%
222
 
8.2%
118
 
6.7%

46 Shopping on the website helps you fulfill certain roles
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
88 
3
88 
5
38 
1
33 
2
22 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row5
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

Length

2022-06-09T21:39:09.910969image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:09.992751image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

Most occurring characters

ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
488
32.7%
388
32.7%
538
14.1%
133
 
12.3%
222
 
8.2%

47 Getting value for money spent
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
4
149 
5
82 
3
38 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters269
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row4
4th row4
5th row5

Common Values

ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%

Length

2022-06-09T21:39:10.071540image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:10.147337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%

Most occurring characters

ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number269
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%

Most occurring scripts

ValueCountFrequency (%)
Common269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4149
55.4%
582
30.5%
338
 
14.1%
Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
82 
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com
44 
Amazon.in, Flipkart.com
32 
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com
29 
Amazon.in, Flipkart.com, Snapdeal.com
27 
Other values (4)
55 

Length

Max length60
Median length48
Mean length42.62081784
Min length9

Characters and Unicode

Total characters11465
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in, Paytm.com
2nd rowAmazon.in, Flipkart.com, Myntra.com, Snapdeal.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
5th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com82
30.5%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com44
16.4%
Amazon.in, Flipkart.com32
 
11.9%
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com29
 
10.8%
Amazon.in, Flipkart.com, Snapdeal.com27
 
10.0%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in16
 
5.9%
Amazon.in, Paytm.com12
 
4.5%
Amazon.in, Flipkart.com, Paytm.com7
 
2.6%

Length

2022-06-09T21:39:10.224168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:10.325892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in269
27.8%
flipkart.com221
22.8%
snapdeal.com182
18.8%
paytm.com150
15.5%
myntra.com146
15.1%

Most occurring characters

ValueCountFrequency (%)
a1150
 
10.0%
m1118
 
9.8%
o968
 
8.4%
.968
 
8.4%
n866
 
7.6%
,699
 
6.1%
699
 
6.1%
c699
 
6.1%
t517
 
4.5%
i490
 
4.3%
Other values (13)3291
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8131
70.9%
Other Punctuation1667
 
14.5%
Uppercase Letter968
 
8.4%
Space Separator699
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1150
14.1%
m1118
13.7%
o968
11.9%
n866
10.7%
c699
8.6%
t517
6.4%
i490
6.0%
l403
 
5.0%
p403
 
5.0%
r367
 
4.5%
Other values (5)1150
14.1%
Uppercase Letter
ValueCountFrequency (%)
A269
27.8%
F221
22.8%
S182
18.8%
P150
15.5%
M146
15.1%
Other Punctuation
ValueCountFrequency (%)
.968
58.1%
,699
41.9%
Space Separator
ValueCountFrequency (%)
699
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9099
79.4%
Common2366
 
20.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1150
12.6%
m1118
12.3%
o968
10.6%
n866
9.5%
c699
 
7.7%
t517
 
5.7%
i490
 
5.4%
l403
 
4.4%
p403
 
4.4%
r367
 
4.0%
Other values (10)2118
23.3%
Common
ValueCountFrequency (%)
.968
40.9%
,699
29.5%
699
29.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII11465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a1150
 
10.0%
m1118
 
9.8%
o968
 
8.4%
.968
 
8.4%
n866
 
7.6%
,699
 
6.1%
699
 
6.1%
c699
 
6.1%
t517
 
4.5%
i490
 
4.3%
Other values (13)3291
28.7%

Easy to use website or application
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
64 
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com
44 
Amazon.in, Flipkart.com
44 
Amazon.in
29 
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com
22 
Other values (5)
66 

Length

Max length60
Median length48
Mean length37.07806691
Min length9

Characters and Unicode

Total characters9974
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPaytm.com
2nd rowAmazon.in, Flipkart.com, Myntra.com, Snapdeal.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
5th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com64
23.8%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com44
16.4%
Amazon.in, Flipkart.com44
16.4%
Amazon.in29
10.8%
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com22
 
8.2%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in, Flipkart.com, Myntra.com19
 
7.1%
Paytm.com12
 
4.5%
Flipkart.com8
 
3.0%
Amazon.in, Paytm.com7
 
2.6%

Length

2022-06-09T21:39:10.636171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:10.737899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in249
29.2%
flipkart.com201
23.6%
myntra.com147
17.3%
snapdeal.com130
15.3%
paytm.com125
14.7%

Most occurring characters

ValueCountFrequency (%)
a982
 
9.8%
m977
 
9.8%
o852
 
8.5%
.852
 
8.5%
n775
 
7.8%
c603
 
6.0%
,583
 
5.8%
583
 
5.8%
t473
 
4.7%
i450
 
4.5%
Other values (13)2844
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7104
71.2%
Other Punctuation1435
 
14.4%
Uppercase Letter852
 
8.5%
Space Separator583
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a982
13.8%
m977
13.8%
o852
12.0%
n775
10.9%
c603
8.5%
t473
6.7%
i450
6.3%
r348
 
4.9%
l331
 
4.7%
p331
 
4.7%
Other values (5)982
13.8%
Uppercase Letter
ValueCountFrequency (%)
A249
29.2%
F201
23.6%
M147
17.3%
S130
15.3%
P125
14.7%
Other Punctuation
ValueCountFrequency (%)
.852
59.4%
,583
40.6%
Space Separator
ValueCountFrequency (%)
583
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7956
79.8%
Common2018
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a982
12.3%
m977
12.3%
o852
10.7%
n775
9.7%
c603
 
7.6%
t473
 
5.9%
i450
 
5.7%
r348
 
4.4%
l331
 
4.2%
p331
 
4.2%
Other values (10)1834
23.1%
Common
ValueCountFrequency (%)
.852
42.2%
,583
28.9%
583
28.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII9974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a982
 
9.8%
m977
 
9.8%
o852
 
8.5%
.852
 
8.5%
n775
 
7.8%
c603
 
6.0%
,583
 
5.8%
583
 
5.8%
t473
 
4.7%
i450
 
4.5%
Other values (13)2844
28.5%

Visual appealing web-page layout
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com
87 
Amazon.in
44 
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
36 
Amazon.in, Paytm.com, Myntra.com
20 
Amazon.in, Myntra.com
15 
Other values (5)
67 

Length

Max length60
Median length48
Mean length27.43494424
Min length9

Characters and Unicode

Total characters7380
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowAmazon.in, Myntra.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
5th rowMyntra.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com87
32.3%
Amazon.in44
16.4%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com36
13.4%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in, Myntra.com15
 
5.6%
Myntra.com15
 
5.6%
Flipkart.com, Myntra.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Flipkart.com12
 
4.5%
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com11
 
4.1%

Length

2022-06-09T21:39:10.863561image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:10.964291image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in227
35.2%
flipkart.com175
27.1%
myntra.com115
17.8%
paytm.com67
 
10.4%
snapdeal.com61
 
9.5%

Most occurring characters

ValueCountFrequency (%)
m712
 
9.6%
a706
 
9.6%
o645
 
8.7%
.645
 
8.7%
n630
 
8.5%
c418
 
5.7%
i402
 
5.4%
,376
 
5.1%
376
 
5.1%
t357
 
4.8%
Other values (13)2113
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5338
72.3%
Other Punctuation1021
 
13.8%
Uppercase Letter645
 
8.7%
Space Separator376
 
5.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m712
13.3%
a706
13.2%
o645
12.1%
n630
11.8%
c418
7.8%
i402
7.5%
t357
6.7%
r290
5.4%
l236
 
4.4%
p236
 
4.4%
Other values (5)706
13.2%
Uppercase Letter
ValueCountFrequency (%)
A227
35.2%
F175
27.1%
M115
17.8%
P67
 
10.4%
S61
 
9.5%
Other Punctuation
ValueCountFrequency (%)
.645
63.2%
,376
36.8%
Space Separator
ValueCountFrequency (%)
376
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5983
81.1%
Common1397
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
m712
11.9%
a706
11.8%
o645
10.8%
n630
10.5%
c418
 
7.0%
i402
 
6.7%
t357
 
6.0%
r290
 
4.8%
l236
 
3.9%
p236
 
3.9%
Other values (10)1351
22.6%
Common
ValueCountFrequency (%)
.645
46.2%
,376
26.9%
376
26.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m712
 
9.6%
a706
 
9.6%
o645
 
8.7%
.645
 
8.7%
n630
 
8.5%
c418
 
5.7%
i402
 
5.4%
,376
 
5.1%
376
 
5.1%
t357
 
4.8%
Other values (13)2113
28.6%

Wild variety of product on offer
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com
130 
Amazon.in
43 
Amazon.in, Myntra.com
20 
Flipkart.com, Myntra.com
15 
Myntra.com
15 
Other values (4)
46 

Length

Max length49
Median length34
Mean length20.9739777
Min length9

Characters and Unicode

Total characters5642
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowFlipkart.com, Myntra.com
3rd rowAmazon.in, Myntra.com
4th rowAmazon.in, Flipkart.com
5th rowMyntra.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com130
48.3%
Amazon.in43
 
16.0%
Amazon.in, Myntra.com20
 
7.4%
Flipkart.com, Myntra.com15
 
5.6%
Myntra.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Amazon.in, Flipkart.com, Paytm.com13
 
4.8%
Flipkart.com12
 
4.5%
Paytm.com7
 
2.6%

Length

2022-06-09T21:39:11.090954image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:11.192682image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in220
43.8%
flipkart.com184
36.7%
myntra.com64
 
12.7%
paytm.com20
 
4.0%
snapdeal.com14
 
2.8%

Most occurring characters

ValueCountFrequency (%)
m522
 
9.3%
n518
 
9.2%
a516
 
9.1%
o502
 
8.9%
.502
 
8.9%
i404
 
7.2%
c282
 
5.0%
t268
 
4.8%
r248
 
4.4%
,233
 
4.1%
Other values (13)1647
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4172
73.9%
Other Punctuation735
 
13.0%
Uppercase Letter502
 
8.9%
Space Separator233
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m522
12.5%
n518
12.4%
a516
12.4%
o502
12.0%
i404
9.7%
c282
6.8%
t268
6.4%
r248
5.9%
z220
5.3%
l198
 
4.7%
Other values (5)494
11.8%
Uppercase Letter
ValueCountFrequency (%)
A220
43.8%
F184
36.7%
M64
 
12.7%
P20
 
4.0%
S14
 
2.8%
Other Punctuation
ValueCountFrequency (%)
.502
68.3%
,233
31.7%
Space Separator
ValueCountFrequency (%)
233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4674
82.8%
Common968
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
m522
11.2%
n518
11.1%
a516
11.0%
o502
10.7%
i404
8.6%
c282
 
6.0%
t268
 
5.7%
r248
 
5.3%
A220
 
4.7%
z220
 
4.7%
Other values (10)974
20.8%
Common
ValueCountFrequency (%)
.502
51.9%
,233
24.1%
233
24.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m522
 
9.3%
n518
 
9.2%
a516
 
9.1%
o502
 
8.9%
.502
 
8.9%
i404
 
7.2%
c282
 
5.0%
t268
 
4.8%
r248
 
4.4%
,233
 
4.1%
Other values (13)1647
29.2%

Complete, relevant description information of products
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com
100 
Amazon.in
43 
Amazon.in, Flipkart.com, Paytm.com
24 
Amazon.in, Paytm.com, Myntra.com
20 
Amazon.in, Flipkart.com, Myntra.com
15 
Other values (6)
67 

Length

Max length60
Median length49
Mean length26.16728625
Min length9

Characters and Unicode

Total characters7039
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSnapdeal.com
2nd rowAmazon.in, Flipkart.com, Myntra.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com
5th rowAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com100
37.2%
Amazon.in43
16.0%
Amazon.in, Flipkart.com, Paytm.com24
 
8.9%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in, Flipkart.com, Myntra.com15
 
5.6%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Snapdeal.com12
 
4.5%
Flipkart.com, Snapdeal.com11
 
4.1%
Flipkart.com8
 
3.0%

Length

2022-06-09T21:39:11.300392image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
amazon.in238
38.8%
flipkart.com194
31.6%
myntra.com64
 
10.4%
paytm.com59
 
9.6%
snapdeal.com59
 
9.6%

Most occurring characters

ValueCountFrequency (%)
a673
 
9.6%
m673
 
9.6%
o614
 
8.7%
.614
 
8.7%
n599
 
8.5%
i432
 
6.1%
c376
 
5.3%
,345
 
4.9%
345
 
4.9%
t317
 
4.5%
Other values (13)2051
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5121
72.8%
Other Punctuation959
 
13.6%
Uppercase Letter614
 
8.7%
Space Separator345
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a673
13.1%
m673
13.1%
o614
12.0%
n599
11.7%
i432
8.4%
c376
7.3%
t317
6.2%
r258
 
5.0%
l253
 
4.9%
p253
 
4.9%
Other values (5)673
13.1%
Uppercase Letter
ValueCountFrequency (%)
A238
38.8%
F194
31.6%
M64
 
10.4%
P59
 
9.6%
S59
 
9.6%
Other Punctuation
ValueCountFrequency (%)
.614
64.0%
,345
36.0%
Space Separator
ValueCountFrequency (%)
345
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5735
81.5%
Common1304
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a673
11.7%
m673
11.7%
o614
10.7%
n599
10.4%
i432
 
7.5%
c376
 
6.6%
t317
 
5.5%
r258
 
4.5%
l253
 
4.4%
p253
 
4.4%
Other values (10)1287
22.4%
Common
ValueCountFrequency (%)
.614
47.1%
,345
26.5%
345
26.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII7039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a673
 
9.6%
m673
 
9.6%
o614
 
8.7%
.614
 
8.7%
n599
 
8.5%
i432
 
6.1%
c376
 
5.3%
,345
 
4.9%
345
 
4.9%
t317
 
4.5%
Other values (13)2051
29.1%

Fast loading website speed of website and application
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
51 
Amazon.in, Paytm.com
44 
Amazon.in, Flipkart.com, Myntra.com
30 
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
30 
Amazon.in, Flipkart.com
30 
Other values (5)
84 

Length

Max length60
Median length35
Mean length28.17843866
Min length9

Characters and Unicode

Total characters7580
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSnapdeal.com
2nd rowAmazon.in, Flipkart.com, Myntra.com
3rd rowAmazon.in, Paytm.com
4th rowAmazon.in, Flipkart.com, Snapdeal.com
5th rowAmazon.in

Common Values

ValueCountFrequency (%)
Amazon.in51
19.0%
Amazon.in, Paytm.com44
16.4%
Amazon.in, Flipkart.com, Myntra.com30
11.2%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com30
11.2%
Amazon.in, Flipkart.com30
11.2%
Amazon.in, Flipkart.com, Snapdeal.com25
9.3%
Amazon.in, Flipkart.com, Paytm.com25
9.3%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Snapdeal.com12
 
4.5%
Flipkart.com8
 
3.0%

Length

2022-06-09T21:39:11.383172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:11.486893image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in249
37.4%
flipkart.com162
24.4%
paytm.com99
 
14.9%
snapdeal.com81
 
12.2%
myntra.com74
 
11.1%

Most occurring characters

ValueCountFrequency (%)
m764
 
10.1%
a746
 
9.8%
o665
 
8.8%
.665
 
8.8%
n653
 
8.6%
c416
 
5.5%
i411
 
5.4%
,396
 
5.2%
396
 
5.2%
t335
 
4.4%
Other values (13)2133
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5458
72.0%
Other Punctuation1061
 
14.0%
Uppercase Letter665
 
8.8%
Space Separator396
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m764
14.0%
a746
13.7%
o665
12.2%
n653
12.0%
c416
7.6%
i411
7.5%
t335
6.1%
z249
 
4.6%
l243
 
4.5%
p243
 
4.5%
Other values (5)733
13.4%
Uppercase Letter
ValueCountFrequency (%)
A249
37.4%
F162
24.4%
P99
 
14.9%
S81
 
12.2%
M74
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.665
62.7%
,396
37.3%
Space Separator
ValueCountFrequency (%)
396
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6123
80.8%
Common1457
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
m764
12.5%
a746
12.2%
o665
10.9%
n653
10.7%
c416
 
6.8%
i411
 
6.7%
t335
 
5.5%
A249
 
4.1%
z249
 
4.1%
l243
 
4.0%
Other values (10)1392
22.7%
Common
ValueCountFrequency (%)
.665
45.6%
,396
27.2%
396
27.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII7580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m764
 
10.1%
a746
 
9.8%
o665
 
8.8%
.665
 
8.8%
n653
 
8.6%
c416
 
5.5%
i411
 
5.4%
,396
 
5.2%
396
 
5.2%
t335
 
4.4%
Other values (13)2133
28.1%

Reliability of the website or application
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
61 
Amazon.in, Flipkart.com
50 
Amazon.in, Flipkart.com, Paytm.com
36 
Amazon.in, Paytm.com, Myntra.com
35 
Amazon.in, Flipkart.com, Snapdeal.com
18 
Other values (5)
69 

Length

Max length49
Median length37
Mean length24.00371747
Min length9

Characters and Unicode

Total characters6457
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPaytm.com
2nd rowMyntra.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Paytm.com
5th rowAmazon.in, Paytm.com, Myntra.com

Common Values

ValueCountFrequency (%)
Amazon.in61
22.7%
Amazon.in, Flipkart.com50
18.6%
Amazon.in, Flipkart.com, Paytm.com36
13.4%
Amazon.in, Paytm.com, Myntra.com35
13.0%
Amazon.in, Flipkart.com, Snapdeal.com18
 
6.7%
Myntra.com15
 
5.6%
Flipkart.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Amazon.in, Flipkart.com, Paytm.com, Snapdeal.com13
 
4.8%
Paytm.com12
 
4.5%

Length

2022-06-09T21:39:11.619508image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:11.724228image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in227
39.3%
flipkart.com146
25.3%
paytm.com96
16.6%
myntra.com64
 
11.1%
snapdeal.com45
 
7.8%

Most occurring characters

ValueCountFrequency (%)
m674
 
10.4%
a623
 
9.6%
o578
 
9.0%
.578
 
9.0%
n563
 
8.7%
i373
 
5.8%
c351
 
5.4%
,309
 
4.8%
309
 
4.8%
t306
 
4.7%
Other values (13)1793
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4683
72.5%
Other Punctuation887
 
13.7%
Uppercase Letter578
 
9.0%
Space Separator309
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m674
14.4%
a623
13.3%
o578
12.3%
n563
12.0%
i373
8.0%
c351
7.5%
t306
6.5%
z227
 
4.8%
r210
 
4.5%
l191
 
4.1%
Other values (5)587
12.5%
Uppercase Letter
ValueCountFrequency (%)
A227
39.3%
F146
25.3%
P96
16.6%
M64
 
11.1%
S45
 
7.8%
Other Punctuation
ValueCountFrequency (%)
.578
65.2%
,309
34.8%
Space Separator
ValueCountFrequency (%)
309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5261
81.5%
Common1196
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
m674
12.8%
a623
11.8%
o578
11.0%
n563
10.7%
i373
 
7.1%
c351
 
6.7%
t306
 
5.8%
A227
 
4.3%
z227
 
4.3%
r210
 
4.0%
Other values (10)1129
21.5%
Common
ValueCountFrequency (%)
.578
48.3%
,309
25.8%
309
25.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6457
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m674
 
10.4%
a623
 
9.6%
o578
 
9.0%
.578
 
9.0%
n563
 
8.7%
i373
 
5.8%
c351
 
5.4%
,309
 
4.8%
309
 
4.8%
t306
 
4.7%
Other values (13)1793
27.8%

Quickness to complete purchase
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.com
66 
Amazon.com, Flipkart.com, Paytm.com
47 
Amazon.com, Flipkart.com
37 
Amazon.com, Flipkart.com, Myntra.com
30 
Paytm.com
25 
Other values (4)
64 

Length

Max length57
Median length35
Mean length24.79182156
Min length9

Characters and Unicode

Total characters6669
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPaytm.com
2nd rowAmazon.com, Flipkart.com, Myntra.com
3rd rowAmazon.com, Paytm.com, Myntra.com
4th rowAmazon.com, Flipkart.com, Paytm.com
5th rowAmazon.com, Flipkart.com, Paytm.com, Myntra.com, Snapdeal

Common Values

ValueCountFrequency (%)
Amazon.com66
24.5%
Amazon.com, Flipkart.com, Paytm.com47
17.5%
Amazon.com, Flipkart.com37
13.8%
Amazon.com, Flipkart.com, Myntra.com30
11.2%
Paytm.com25
 
9.3%
Amazon.com, Paytm.com, Myntra.com20
 
7.4%
Amazon.com, Flipkart.com, Paytm.com, Myntra.com, Snapdeal15
 
5.6%
Flipkart.com15
 
5.6%
Flipkart.com, Myntra.com, Snapdeal14
 
5.2%

Length

2022-06-09T21:39:11.844905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:11.945643image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.com215
36.6%
flipkart.com158
26.9%
paytm.com107
18.2%
myntra.com79
 
13.4%
snapdeal29
 
4.9%

Most occurring characters

ValueCountFrequency (%)
m881
13.2%
o774
11.6%
a617
 
9.3%
.559
 
8.4%
c559
 
8.4%
t344
 
5.2%
n323
 
4.8%
,319
 
4.8%
319
 
4.8%
r237
 
3.6%
Other values (13)1737
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4884
73.2%
Other Punctuation878
 
13.2%
Uppercase Letter588
 
8.8%
Space Separator319
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m881
18.0%
o774
15.8%
a617
12.6%
c559
11.4%
t344
 
7.0%
n323
 
6.6%
r237
 
4.9%
z215
 
4.4%
p187
 
3.8%
l187
 
3.8%
Other values (5)560
11.5%
Uppercase Letter
ValueCountFrequency (%)
A215
36.6%
F158
26.9%
P107
18.2%
M79
 
13.4%
S29
 
4.9%
Other Punctuation
ValueCountFrequency (%)
.559
63.7%
,319
36.3%
Space Separator
ValueCountFrequency (%)
319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5472
82.1%
Common1197
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
m881
16.1%
o774
14.1%
a617
11.3%
c559
10.2%
t344
 
6.3%
n323
 
5.9%
r237
 
4.3%
A215
 
3.9%
z215
 
3.9%
p187
 
3.4%
Other values (10)1120
20.5%
Common
ValueCountFrequency (%)
.559
46.7%
,319
26.6%
319
26.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII6669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m881
13.2%
o774
11.6%
a617
 
9.3%
.559
 
8.4%
c559
 
8.4%
t344
 
5.2%
n323
 
4.8%
,319
 
4.8%
319
 
4.8%
r237
 
3.6%
Other values (13)1737
26.0%

Availability of several payment options
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com
65 
Amazon.in, Flipkart.com, Myntra.com
40 
Amazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.com
39 
Amazon.in
23 
Patym.com, Myntra.com
20 
Other values (6)
82 

Length

Max length60
Median length38
Mean length31.28252788
Min length9

Characters and Unicode

Total characters8415
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPatym.com
2nd rowAmazon.in, Flipkart.com, Myntra.com
3rd rowPatym.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Myntra.com
5th rowAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com65
24.2%
Amazon.in, Flipkart.com, Myntra.com40
14.9%
Amazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.com39
14.5%
Amazon.in23
 
8.6%
Patym.com, Myntra.com20
 
7.4%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com19
 
7.1%
Amazon.in, Flipkart.com, Snapdeal.com18
 
6.7%
Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Patym.com12
 
4.5%
Amazon.in, Patym.com11
 
4.1%

Length

2022-06-09T21:39:12.066353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
amazon.in215
29.8%
flipkart.com203
28.1%
myntra.com132
18.3%
snapdeal.com90
12.5%
patym.com82
 
11.4%

Most occurring characters

ValueCountFrequency (%)
a812
 
9.6%
m804
 
9.6%
o722
 
8.6%
.722
 
8.6%
n652
 
7.7%
c507
 
6.0%
,453
 
5.4%
453
 
5.4%
i418
 
5.0%
t417
 
5.0%
Other values (13)2455
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6065
72.1%
Other Punctuation1175
 
14.0%
Uppercase Letter722
 
8.6%
Space Separator453
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a812
13.4%
m804
13.3%
o722
11.9%
n652
10.8%
c507
8.4%
i418
6.9%
t417
6.9%
r335
5.5%
l293
 
4.8%
p293
 
4.8%
Other values (5)812
13.4%
Uppercase Letter
ValueCountFrequency (%)
A215
29.8%
F203
28.1%
M132
18.3%
S90
12.5%
P82
 
11.4%
Other Punctuation
ValueCountFrequency (%)
.722
61.4%
,453
38.6%
Space Separator
ValueCountFrequency (%)
453
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6787
80.7%
Common1628
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a812
12.0%
m804
11.8%
o722
10.6%
n652
9.6%
c507
 
7.5%
i418
 
6.2%
t417
 
6.1%
r335
 
4.9%
l293
 
4.3%
p293
 
4.3%
Other values (10)1534
22.6%
Common
ValueCountFrequency (%)
.722
44.3%
,453
27.8%
453
27.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a812
 
9.6%
m804
 
9.6%
o722
 
8.6%
.722
 
8.6%
n652
 
7.7%
c507
 
6.0%
,453
 
5.4%
453
 
5.4%
i418
 
5.0%
t417
 
5.0%
Other values (13)2455
29.2%

Speedy order delivery
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
107 
Amazon.in, Flipkart.com
82 
Amazon.in, Flipkart.com, Snapdeal.com
36 
Amazon.in, Flipkart.com, Myntra.com
15 
Flipkart.com
15 

Length

Max length38
Median length37
Mean length20.14126394
Min length9

Characters and Unicode

Total characters5418
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowAmazon.in, Flipkart.com
3rd rowAmazon.in
4th rowAmazon.in, Flipkart.com, Snapdeal.com
5th rowAmazon.in

Common Values

ValueCountFrequency (%)
Amazon.in107
39.8%
Amazon.in, Flipkart.com82
30.5%
Amazon.in, Flipkart.com, Snapdeal.com36
 
13.4%
Amazon.in, Flipkart.com, Myntra.com15
 
5.6%
Flipkart.com15
 
5.6%
Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%

Length

2022-06-09T21:39:12.144147image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:12.232907image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in240
49.9%
flipkart.com162
33.7%
snapdeal.com50
 
10.4%
myntra.com29
 
6.0%

Most occurring characters

ValueCountFrequency (%)
n559
 
10.3%
a531
 
9.8%
m481
 
8.9%
o481
 
8.9%
.481
 
8.9%
i402
 
7.4%
c241
 
4.4%
A240
 
4.4%
z240
 
4.4%
p212
 
3.9%
Other values (12)1550
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4032
74.4%
Other Punctuation693
 
12.8%
Uppercase Letter481
 
8.9%
Space Separator212
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n559
13.9%
a531
13.2%
m481
11.9%
o481
11.9%
i402
10.0%
c241
6.0%
z240
6.0%
p212
 
5.3%
l212
 
5.3%
r191
 
4.7%
Other values (5)482
12.0%
Uppercase Letter
ValueCountFrequency (%)
A240
49.9%
F162
33.7%
S50
 
10.4%
M29
 
6.0%
Other Punctuation
ValueCountFrequency (%)
.481
69.4%
,212
30.6%
Space Separator
ValueCountFrequency (%)
212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4513
83.3%
Common905
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n559
12.4%
a531
11.8%
m481
10.7%
o481
10.7%
i402
8.9%
c241
 
5.3%
A240
 
5.3%
z240
 
5.3%
p212
 
4.7%
l212
 
4.7%
Other values (9)914
20.3%
Common
ValueCountFrequency (%)
.481
53.1%
212
23.4%
,212
23.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII5418
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n559
 
10.3%
a531
 
9.8%
m481
 
8.9%
o481
 
8.9%
.481
 
8.9%
i402
 
7.4%
c241
 
4.4%
A240
 
4.4%
z240
 
4.4%
p212
 
3.9%
Other values (12)1550
28.6%

Privacy of customers’ information
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
71 
Amazon.in, Flipkart.com
54 
Amazon.in, Flipkart.com, Myntra.com
25 
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
24 
Paytm.com
18 
Other values (6)
77 

Length

Max length60
Median length49
Mean length23.44609665
Min length9

Characters and Unicode

Total characters6307
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowMyntra.com
3rd rowAmazon.in
4th rowAmazon.in, Flipkart.com, Myntra.com
5th rowAmazon.in, Paytm.com

Common Values

ValueCountFrequency (%)
Amazon.in71
26.4%
Amazon.in, Flipkart.com54
20.1%
Amazon.in, Flipkart.com, Myntra.com25
 
9.3%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com24
 
8.9%
Paytm.com18
 
6.7%
Myntra.com15
 
5.6%
Amazon.in, Paytm.com15
 
5.6%
Flipkart.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%
Amazon.in, Flipkart.com, Paytm.com11
 
4.1%

Length

2022-06-09T21:39:12.331642image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
amazon.in221
39.3%
flipkart.com150
26.7%
myntra.com78
 
13.9%
paytm.com68
 
12.1%
snapdeal.com45
 
8.0%

Most occurring characters

ValueCountFrequency (%)
m630
 
10.0%
a607
 
9.6%
n565
 
9.0%
o562
 
8.9%
.562
 
8.9%
i371
 
5.9%
c341
 
5.4%
t296
 
4.7%
,293
 
4.6%
293
 
4.6%
Other values (13)1787
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4597
72.9%
Other Punctuation855
 
13.6%
Uppercase Letter562
 
8.9%
Space Separator293
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m630
13.7%
a607
13.2%
n565
12.3%
o562
12.2%
i371
8.1%
c341
7.4%
t296
6.4%
r228
 
5.0%
z221
 
4.8%
l195
 
4.2%
Other values (5)581
12.6%
Uppercase Letter
ValueCountFrequency (%)
A221
39.3%
F150
26.7%
M78
 
13.9%
P68
 
12.1%
S45
 
8.0%
Other Punctuation
ValueCountFrequency (%)
.562
65.7%
,293
34.3%
Space Separator
ValueCountFrequency (%)
293
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5159
81.8%
Common1148
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
m630
12.2%
a607
11.8%
n565
11.0%
o562
10.9%
i371
 
7.2%
c341
 
6.6%
t296
 
5.7%
r228
 
4.4%
A221
 
4.3%
z221
 
4.3%
Other values (10)1117
21.7%
Common
ValueCountFrequency (%)
.562
49.0%
,293
25.5%
293
25.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII6307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m630
 
10.0%
a607
 
9.6%
n565
 
9.0%
o562
 
8.9%
.562
 
8.9%
i371
 
5.9%
c341
 
5.4%
t296
 
4.7%
,293
 
4.6%
293
 
4.6%
Other values (13)1787
28.3%

Security of customer financial information
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
51 
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com
42 
Flipkart.com
33 
Amazon.in, Flipkart.com, Snapdeal.com
25 
Amazon.in, Flipkart.com
24 
Other values (6)
94 

Length

Max length60
Median length37
Mean length27.04089219
Min length9

Characters and Unicode

Total characters7274
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowMyntra.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com, Snapdeal.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Amazon.in51
19.0%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com42
15.6%
Flipkart.com33
12.3%
Amazon.in, Flipkart.com, Snapdeal.com25
9.3%
Amazon.in, Flipkart.com24
8.9%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in, Snapdeal.com19
 
7.1%
Myntra.com15
 
5.6%
Paytm.com15
 
5.6%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com14
 
5.2%

Length

2022-06-09T21:39:12.413424image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
amazon.in206
32.5%
flipkart.com149
23.5%
snapdeal.com100
15.8%
myntra.com91
14.4%
paytm.com88
13.9%

Most occurring characters

ValueCountFrequency (%)
a734
 
10.1%
m722
 
9.9%
o634
 
8.7%
.634
 
8.7%
n603
 
8.3%
c428
 
5.9%
,365
 
5.0%
365
 
5.0%
i355
 
4.9%
t328
 
4.5%
Other values (13)2106
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5276
72.5%
Other Punctuation999
 
13.7%
Uppercase Letter634
 
8.7%
Space Separator365
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a734
13.9%
m722
13.7%
o634
12.0%
n603
11.4%
c428
8.1%
i355
6.7%
t328
6.2%
l249
 
4.7%
p249
 
4.7%
r240
 
4.5%
Other values (5)734
13.9%
Uppercase Letter
ValueCountFrequency (%)
A206
32.5%
F149
23.5%
S100
15.8%
M91
14.4%
P88
13.9%
Other Punctuation
ValueCountFrequency (%)
.634
63.5%
,365
36.5%
Space Separator
ValueCountFrequency (%)
365
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5910
81.2%
Common1364
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a734
12.4%
m722
12.2%
o634
10.7%
n603
10.2%
c428
 
7.2%
i355
 
6.0%
t328
 
5.5%
l249
 
4.2%
p249
 
4.2%
r240
 
4.1%
Other values (10)1368
23.1%
Common
ValueCountFrequency (%)
.634
46.5%
,365
26.8%
365
26.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII7274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a734
 
10.1%
m722
 
9.9%
o634
 
8.7%
.634
 
8.7%
n603
 
8.3%
c428
 
5.9%
,365
 
5.0%
365
 
5.0%
i355
 
4.9%
t328
 
4.5%
Other values (13)2106
29.0%

Perceived Trustworthiness
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
76 
Amazon.in, Flipkart.com, Snapdeal.com
36 
Amazon.in, Myntra.com
35 
Amazon.in, Flipkart.com
31 
Flipkart.com
27 
Other values (4)
64 

Length

Max length60
Median length37
Mean length23.48327138
Min length9

Characters and Unicode

Total characters6317
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowMyntra.com
3rd rowAmazon.in, Myntra.com
4th rowAmazon.in, Flipkart.com, Snapdeal.com
5th rowAmazon.in, Myntra.com

Common Values

ValueCountFrequency (%)
Amazon.in76
28.3%
Amazon.in, Flipkart.com, Snapdeal.com36
13.4%
Amazon.in, Myntra.com35
13.0%
Amazon.in, Flipkart.com31
11.5%
Flipkart.com27
 
10.0%
Amazon.in, Flipkart.com, Myntra.com, Snapdeal.com25
 
9.3%
Myntra.com15
 
5.6%
Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.com13
 
4.8%
Amazon.in, Flipkart.com, Paytm.com11
 
4.1%

Length

2022-06-09T21:39:12.494207image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:12.593940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in227
40.8%
flipkart.com143
25.7%
myntra.com88
 
15.8%
snapdeal.com74
 
13.3%
paytm.com24
 
4.3%

Most occurring characters

ValueCountFrequency (%)
a630
 
10.0%
n616
 
9.8%
m580
 
9.2%
o556
 
8.8%
.556
 
8.8%
i370
 
5.9%
c329
 
5.2%
,287
 
4.5%
287
 
4.5%
t255
 
4.0%
Other values (13)1851
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4631
73.3%
Other Punctuation843
 
13.3%
Uppercase Letter556
 
8.8%
Space Separator287
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a630
13.6%
n616
13.3%
m580
12.5%
o556
12.0%
i370
8.0%
c329
7.1%
t255
5.5%
r231
 
5.0%
z227
 
4.9%
l217
 
4.7%
Other values (5)620
13.4%
Uppercase Letter
ValueCountFrequency (%)
A227
40.8%
F143
25.7%
M88
 
15.8%
S74
 
13.3%
P24
 
4.3%
Other Punctuation
ValueCountFrequency (%)
.556
66.0%
,287
34.0%
Space Separator
ValueCountFrequency (%)
287
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5187
82.1%
Common1130
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a630
12.1%
n616
11.9%
m580
11.2%
o556
10.7%
i370
 
7.1%
c329
 
6.3%
t255
 
4.9%
r231
 
4.5%
A227
 
4.4%
z227
 
4.4%
Other values (10)1166
22.5%
Common
ValueCountFrequency (%)
.556
49.2%
,287
25.4%
287
25.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII6317
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a630
 
10.0%
n616
 
9.8%
m580
 
9.2%
o556
 
8.8%
.556
 
8.8%
i370
 
5.9%
c329
 
5.2%
,287
 
4.5%
287
 
4.5%
t255
 
4.0%
Other values (13)1851
29.3%

Presence of online assistance through multi-channel
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com, Myntra.com, Snapdeal
61 
Amazon.in
60 
Amazon.in, Flipkart.com
39 
Amazon.in, Snapdeal
26 
Myntra.com
20 
Other values (5)
63 

Length

Max length45
Median length34
Mean length23.65055762
Min length9

Characters and Unicode

Total characters6362
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPaytm.com
2nd rowAmazon.in, Flipkart.com, Myntra.com
3rd rowMyntra.com
4th rowAmazon.in, Flipkart.com, Myntra.com, Snapdeal
5th rowAmazon.in, Myntra.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com, Myntra.com, Snapdeal61
22.7%
Amazon.in60
22.3%
Amazon.in, Flipkart.com39
14.5%
Amazon.in, Snapdeal26
9.7%
Myntra.com20
 
7.4%
Amazon.in, Flipkart.com, Myntra.com15
 
5.6%
Amazon.in, Myntra.com15
 
5.6%
Amazon.in, Flipkart.com, Paytm.com13
 
4.8%
Paytm.com12
 
4.5%
Flipkart.com8
 
3.0%

Length

2022-06-09T21:39:12.718612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:12.821332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in229
38.9%
flipkart.com136
23.1%
myntra.com111
18.9%
snapdeal87
 
14.8%
paytm.com25
 
4.3%

Most occurring characters

ValueCountFrequency (%)
a675
 
10.6%
n656
 
10.3%
m526
 
8.3%
o501
 
7.9%
.501
 
7.9%
i365
 
5.7%
,319
 
5.0%
319
 
5.0%
c272
 
4.3%
t272
 
4.3%
Other values (13)1956
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4635
72.9%
Other Punctuation820
 
12.9%
Uppercase Letter588
 
9.2%
Space Separator319
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a675
14.6%
n656
14.2%
m526
11.3%
o501
10.8%
i365
7.9%
c272
5.9%
t272
5.9%
r247
 
5.3%
z229
 
4.9%
l223
 
4.8%
Other values (5)669
14.4%
Uppercase Letter
ValueCountFrequency (%)
A229
38.9%
F136
23.1%
M111
18.9%
S87
 
14.8%
P25
 
4.3%
Other Punctuation
ValueCountFrequency (%)
.501
61.1%
,319
38.9%
Space Separator
ValueCountFrequency (%)
319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5223
82.1%
Common1139
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a675
12.9%
n656
12.6%
m526
10.1%
o501
9.6%
i365
 
7.0%
c272
 
5.2%
t272
 
5.2%
r247
 
4.7%
A229
 
4.4%
z229
 
4.4%
Other values (10)1251
24.0%
Common
ValueCountFrequency (%)
.501
44.0%
,319
28.0%
319
28.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a675
 
10.6%
n656
 
10.3%
m526
 
8.3%
o501
 
7.9%
.501
 
7.9%
i365
 
5.7%
,319
 
5.0%
319
 
5.0%
c272
 
4.3%
t272
 
4.3%
Other values (13)1956
30.7%

Longer time to get logged in (promotion, sales period)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
57 
Amazon.in, Flipkart.com
38 
Paytm.com
38 
Myntra.com
35 
Amazon.in, Flipkart.com, Snapdeal.com
29 
Other values (5)
72 

Length

Max length37
Median length23
Mean length17.07806691
Min length9

Characters and Unicode

Total characters4594
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowAmazon.in, Flipkart.com
3rd rowMyntra.com
4th rowSnapdeal.com
5th rowFlipkart.com, Paytm.com

Common Values

ValueCountFrequency (%)
Amazon.in57
21.2%
Amazon.in, Flipkart.com38
14.1%
Paytm.com38
14.1%
Myntra.com35
13.0%
Amazon.in, Flipkart.com, Snapdeal.com29
10.8%
Snapdeal.com25
9.3%
Flipkart.com, Paytm.com15
 
5.6%
Flipkart.com, Paytm.com, Snapdeal.com13
 
4.8%
Amazon.in, Paytm.com11
 
4.1%
Flipkart.com8
 
3.0%

Length

2022-06-09T21:39:12.938018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:13.039748image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in135
32.4%
flipkart.com103
24.7%
paytm.com77
18.5%
snapdeal.com67
16.1%
myntra.com35
 
8.4%

Most occurring characters

ValueCountFrequency (%)
m494
 
10.8%
a484
 
10.5%
o417
 
9.1%
.417
 
9.1%
n372
 
8.1%
c282
 
6.1%
i238
 
5.2%
t215
 
4.7%
l170
 
3.7%
p170
 
3.7%
Other values (13)1335
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3464
75.4%
Other Punctuation565
 
12.3%
Uppercase Letter417
 
9.1%
Space Separator148
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m494
14.3%
a484
14.0%
o417
12.0%
n372
10.7%
c282
8.1%
i238
6.9%
t215
6.2%
l170
 
4.9%
p170
 
4.9%
r138
 
4.0%
Other values (5)484
14.0%
Uppercase Letter
ValueCountFrequency (%)
A135
32.4%
F103
24.7%
P77
18.5%
S67
16.1%
M35
 
8.4%
Other Punctuation
ValueCountFrequency (%)
.417
73.8%
,148
 
26.2%
Space Separator
ValueCountFrequency (%)
148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3881
84.5%
Common713
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
m494
12.7%
a484
12.5%
o417
10.7%
n372
9.6%
c282
 
7.3%
i238
 
6.1%
t215
 
5.5%
l170
 
4.4%
p170
 
4.4%
r138
 
3.6%
Other values (10)901
23.2%
Common
ValueCountFrequency (%)
.417
58.5%
,148
 
20.8%
148
 
20.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII4594
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m494
 
10.8%
a484
 
10.5%
o417
 
9.1%
.417
 
9.1%
n372
 
8.1%
c282
 
6.1%
i238
 
5.2%
t215
 
4.7%
l170
 
3.7%
p170
 
3.7%
Other values (13)1335
29.1%
Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in, Flipkart.com
60 
Amazon.in
39 
Myntra.com
35 
Snapdeal.com
34 
Myntra.com, Snapdeal.com
25 
Other values (5)
76 

Length

Max length35
Median length24
Mean length17.27881041
Min length9

Characters and Unicode

Total characters4648
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowMyntra.com
3rd rowMyntra.com
4th rowMyntra.com, Snapdeal.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Amazon.in, Flipkart.com60
22.3%
Amazon.in39
14.5%
Myntra.com35
13.0%
Snapdeal.com34
12.6%
Myntra.com, Snapdeal.com25
9.3%
Flipkart.com, Snapdeal.com19
 
7.1%
Paytm.com15
 
5.6%
Flipkart.com15
 
5.6%
Amazon.in, Myntra.com, Snapdeal.com14
 
5.2%
Amazon.in, Paytm.com13
 
4.8%

Length

2022-06-09T21:39:13.159429image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:13.260156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in126
30.4%
flipkart.com94
22.7%
snapdeal.com92
22.2%
myntra.com74
17.9%
paytm.com28
 
6.8%

Most occurring characters

ValueCountFrequency (%)
a506
 
10.9%
m442
 
9.5%
n418
 
9.0%
o414
 
8.9%
.414
 
8.9%
c288
 
6.2%
i220
 
4.7%
t196
 
4.2%
l186
 
4.0%
p186
 
4.0%
Other values (13)1378
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3530
75.9%
Other Punctuation559
 
12.0%
Uppercase Letter414
 
8.9%
Space Separator145
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a506
14.3%
m442
12.5%
n418
11.8%
o414
11.7%
c288
8.2%
i220
6.2%
t196
 
5.6%
l186
 
5.3%
p186
 
5.3%
r168
 
4.8%
Other values (5)506
14.3%
Uppercase Letter
ValueCountFrequency (%)
A126
30.4%
F94
22.7%
S92
22.2%
M74
17.9%
P28
 
6.8%
Other Punctuation
ValueCountFrequency (%)
.414
74.1%
,145
 
25.9%
Space Separator
ValueCountFrequency (%)
145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3944
84.9%
Common704
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a506
12.8%
m442
11.2%
n418
10.6%
o414
10.5%
c288
 
7.3%
i220
 
5.6%
t196
 
5.0%
l186
 
4.7%
p186
 
4.7%
r168
 
4.3%
Other values (10)920
23.3%
Common
ValueCountFrequency (%)
.414
58.8%
,145
 
20.6%
145
 
20.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a506
 
10.9%
m442
 
9.5%
n418
 
9.0%
o414
 
8.9%
.414
 
8.9%
c288
 
6.2%
i220
 
4.7%
t196
 
4.2%
l186
 
4.0%
p186
 
4.0%
Other values (13)1378
29.6%

Late declaration of price (promotion, sales period)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Myntra.com
75 
Paytm.com
52 
snapdeal.com
41 
Flipkart.com
38 
Amazon.in
38 
Other values (3)
25 

Length

Max length23
Median length20
Mean length11.31598513
Min length9

Characters and Unicode

Total characters3044
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowsnapdeal.com
3rd rowMyntra.com
4th rowMyntra.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Myntra.com75
27.9%
Paytm.com52
19.3%
snapdeal.com41
15.2%
Flipkart.com38
14.1%
Amazon.in38
14.1%
Amazon.in, Paytm.com13
 
4.8%
Paytm.com, snapdeal.com7
 
2.6%
Amazon.in, Flipkart.com5
 
1.9%

Length

2022-06-09T21:39:13.379876image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:13.476648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
myntra.com75
25.5%
paytm.com72
24.5%
amazon.in56
19.0%
snapdeal.com48
16.3%
flipkart.com43
14.6%

Most occurring characters

ValueCountFrequency (%)
m366
12.0%
a342
11.2%
.294
9.7%
o294
9.7%
c238
 
7.8%
n235
 
7.7%
t190
 
6.2%
y147
 
4.8%
r118
 
3.9%
i99
 
3.3%
Other values (13)721
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2454
80.6%
Other Punctuation319
 
10.5%
Uppercase Letter246
 
8.1%
Space Separator25
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m366
14.9%
a342
13.9%
o294
12.0%
c238
9.7%
n235
9.6%
t190
7.7%
y147
6.0%
r118
 
4.8%
i99
 
4.0%
p91
 
3.7%
Other values (6)334
13.6%
Uppercase Letter
ValueCountFrequency (%)
M75
30.5%
P72
29.3%
A56
22.8%
F43
17.5%
Other Punctuation
ValueCountFrequency (%)
.294
92.2%
,25
 
7.8%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2700
88.7%
Common344
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
m366
13.6%
a342
12.7%
o294
10.9%
c238
8.8%
n235
8.7%
t190
 
7.0%
y147
 
5.4%
r118
 
4.4%
i99
 
3.7%
p91
 
3.4%
Other values (10)580
21.5%
Common
ValueCountFrequency (%)
.294
85.5%
,25
 
7.3%
25
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII3044
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m366
12.0%
a342
11.2%
.294
9.7%
o294
9.7%
c238
 
7.8%
n235
 
7.7%
t190
 
6.2%
y147
 
4.8%
r118
 
3.9%
i99
 
3.3%
Other values (13)721
23.7%

Longer page loading time (promotion, sales period)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Myntra.com
61 
Paytm.com
59 
Flipkart.com
32 
Snapdeal.com
23 
Amazon.in, Flipkart.com
18 
Other values (6)
76 

Length

Max length32
Median length26
Mean length14.11152416
Min length9

Characters and Unicode

Total characters3796
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowSnapdeal.com
3rd rowMyntra.com
4th rowPaytm.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Myntra.com61
22.7%
Paytm.com59
21.9%
Flipkart.com32
11.9%
Snapdeal.com23
 
8.6%
Amazon.in, Flipkart.com18
 
6.7%
Amazon.in16
 
5.9%
Paytm.com, Snapdeal.com15
 
5.6%
Amazon.in, Snapdeal.com14
 
5.2%
Amazon.in, Paytm.com13
 
4.8%
Flipkart.com, Snapdeal.com11
 
4.1%

Length

2022-06-09T21:39:13.579374image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
paytm.com94
26.6%
myntra.com68
19.2%
amazon.in68
19.2%
snapdeal.com63
17.8%
flipkart.com61
17.2%

Most occurring characters

ValueCountFrequency (%)
m448
11.8%
a417
11.0%
o354
 
9.3%
.354
 
9.3%
c286
 
7.5%
n267
 
7.0%
t223
 
5.9%
y162
 
4.3%
r129
 
3.4%
i129
 
3.4%
Other values (13)1027
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2918
76.9%
Other Punctuation439
 
11.6%
Uppercase Letter354
 
9.3%
Space Separator85
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m448
15.4%
a417
14.3%
o354
12.1%
c286
9.8%
n267
9.2%
t223
7.6%
y162
 
5.6%
r129
 
4.4%
i129
 
4.4%
p124
 
4.2%
Other values (5)379
13.0%
Uppercase Letter
ValueCountFrequency (%)
P94
26.6%
A68
19.2%
M68
19.2%
S63
17.8%
F61
17.2%
Other Punctuation
ValueCountFrequency (%)
.354
80.6%
,85
 
19.4%
Space Separator
ValueCountFrequency (%)
85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3272
86.2%
Common524
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
m448
13.7%
a417
12.7%
o354
10.8%
c286
 
8.7%
n267
 
8.2%
t223
 
6.8%
y162
 
5.0%
r129
 
3.9%
i129
 
3.9%
p124
 
3.8%
Other values (10)733
22.4%
Common
ValueCountFrequency (%)
.354
67.6%
,85
 
16.2%
85
 
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3796
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m448
11.8%
a417
11.0%
o354
 
9.3%
.354
 
9.3%
c286
 
7.5%
n267
 
7.0%
t223
 
5.9%
y162
 
4.3%
r129
 
3.4%
i129
 
3.4%
Other values (13)1027
27.1%
Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Snapdeal.com
87 
Amazon.in
62 
Flipkart.com
31 
Amazon.in, Flipkart.com
29 
Paytm.com
25 
Other values (3)
35 

Length

Max length24
Median length23
Mean length13.52788104
Min length9

Characters and Unicode

Total characters3639
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowSnapdeal.com
3rd rowAmazon.in
4th rowPaytm.com
5th rowSnapdeal.com

Common Values

ValueCountFrequency (%)
Snapdeal.com87
32.3%
Amazon.in62
23.0%
Flipkart.com31
 
11.5%
Amazon.in, Flipkart.com29
 
10.8%
Paytm.com25
 
9.3%
Paytm.com, Snapdeal.com15
 
5.6%
Amazon.in, Paytm.com13
 
4.8%
Myntra.com, Snapdeal.com7
 
2.6%

Length

2022-06-09T21:39:13.660158image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:13.756902image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
snapdeal.com109
32.7%
amazon.in104
31.2%
flipkart.com60
18.0%
paytm.com53
15.9%
myntra.com7
 
2.1%

Most occurring characters

ValueCountFrequency (%)
a442
12.1%
m386
 
10.6%
.333
 
9.2%
o333
 
9.2%
n324
 
8.9%
c229
 
6.3%
p169
 
4.6%
l169
 
4.6%
i164
 
4.5%
t120
 
3.3%
Other values (13)970
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2845
78.2%
Other Punctuation397
 
10.9%
Uppercase Letter333
 
9.2%
Space Separator64
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a442
15.5%
m386
13.6%
o333
11.7%
n324
11.4%
c229
8.0%
p169
 
5.9%
l169
 
5.9%
i164
 
5.8%
t120
 
4.2%
d109
 
3.8%
Other values (5)400
14.1%
Uppercase Letter
ValueCountFrequency (%)
S109
32.7%
A104
31.2%
F60
18.0%
P53
15.9%
M7
 
2.1%
Other Punctuation
ValueCountFrequency (%)
.333
83.9%
,64
 
16.1%
Space Separator
ValueCountFrequency (%)
64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3178
87.3%
Common461
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a442
13.9%
m386
12.1%
o333
10.5%
n324
10.2%
c229
 
7.2%
p169
 
5.3%
l169
 
5.3%
i164
 
5.2%
t120
 
3.8%
S109
 
3.4%
Other values (10)733
23.1%
Common
ValueCountFrequency (%)
.333
72.2%
,64
 
13.9%
64
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3639
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a442
12.1%
m386
 
10.6%
.333
 
9.2%
o333
 
9.2%
n324
 
8.9%
c229
 
6.3%
p169
 
4.6%
l169
 
4.6%
i164
 
4.5%
t120
 
3.3%
Other values (13)970
26.7%

Longer delivery period
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Paytm.com
72 
Snapdeal.com
64 
Flipkart.com
44 
Amazon.in
37 
Paytm.com, Snapdeal.com
26 

Length

Max length23
Median length12
Mean length11.65427509
Min length9

Characters and Unicode

Total characters3135
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPaytm.com
2nd rowSnapdeal.com
3rd rowPaytm.com
4th rowPaytm.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Paytm.com72
26.8%
Snapdeal.com64
23.8%
Flipkart.com44
16.4%
Amazon.in37
13.8%
Paytm.com, Snapdeal.com26
 
9.7%
Myntra.com26
 
9.7%

Length

2022-06-09T21:39:13.859591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:13.948354image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
paytm.com98
33.2%
snapdeal.com90
30.5%
flipkart.com44
14.9%
amazon.in37
 
12.5%
myntra.com26
 
8.8%

Most occurring characters

ValueCountFrequency (%)
m393
12.5%
a385
12.3%
.295
 
9.4%
o295
 
9.4%
c258
 
8.2%
n190
 
6.1%
t168
 
5.4%
l134
 
4.3%
p134
 
4.3%
y124
 
4.0%
Other values (13)759
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2493
79.5%
Other Punctuation321
 
10.2%
Uppercase Letter295
 
9.4%
Space Separator26
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m393
15.8%
a385
15.4%
o295
11.8%
c258
10.3%
n190
7.6%
t168
6.7%
l134
 
5.4%
p134
 
5.4%
y124
 
5.0%
e90
 
3.6%
Other values (5)322
12.9%
Uppercase Letter
ValueCountFrequency (%)
P98
33.2%
S90
30.5%
F44
14.9%
A37
 
12.5%
M26
 
8.8%
Other Punctuation
ValueCountFrequency (%)
.295
91.9%
,26
 
8.1%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2788
88.9%
Common347
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m393
14.1%
a385
13.8%
o295
10.6%
c258
9.3%
n190
 
6.8%
t168
 
6.0%
l134
 
4.8%
p134
 
4.8%
y124
 
4.4%
P98
 
3.5%
Other values (10)609
21.8%
Common
ValueCountFrequency (%)
.295
85.0%
,26
 
7.5%
26
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII3135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m393
12.5%
a385
12.3%
.295
 
9.4%
o295
 
9.4%
c258
 
8.2%
n190
 
6.1%
t168
 
5.4%
l134
 
4.3%
p134
 
4.3%
y124
 
4.0%
Other values (13)759
24.2%

Change in website/Application design
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct7
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
96 
Paytm.com
63 
Amazon.in, Flipkart.com
45 
Myntra.com
30 
Flipkart.com
20 
Other values (2)
15 

Length

Max length24
Median length9
Mean length12.15613383
Min length9

Characters and Unicode

Total characters3270
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowAmazon.in
3rd rowPaytm.com
4th rowAmazon.in, Flipkart.com
5th rowAmazon.in

Common Values

ValueCountFrequency (%)
Amazon.in96
35.7%
Paytm.com63
23.4%
Amazon.in, Flipkart.com45
16.7%
Myntra.com30
 
11.2%
Flipkart.com20
 
7.4%
Snapdeal.com8
 
3.0%
Flipkart.com, Myntra.com7
 
2.6%

Length

2022-06-09T21:39:14.047089image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:14.143831image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in141
43.9%
flipkart.com72
22.4%
paytm.com63
19.6%
myntra.com37
 
11.5%
snapdeal.com8
 
2.5%

Most occurring characters

ValueCountFrequency (%)
m384
11.7%
a329
10.1%
n327
10.0%
o321
9.8%
.321
9.8%
i213
 
6.5%
c180
 
5.5%
t172
 
5.3%
A141
 
4.3%
z141
 
4.3%
Other values (13)741
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2524
77.2%
Other Punctuation373
 
11.4%
Uppercase Letter321
 
9.8%
Space Separator52
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m384
15.2%
a329
13.0%
n327
13.0%
o321
12.7%
i213
8.4%
c180
7.1%
t172
6.8%
z141
 
5.6%
r109
 
4.3%
y100
 
4.0%
Other values (5)248
9.8%
Uppercase Letter
ValueCountFrequency (%)
A141
43.9%
F72
22.4%
P63
19.6%
M37
 
11.5%
S8
 
2.5%
Other Punctuation
ValueCountFrequency (%)
.321
86.1%
,52
 
13.9%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2845
87.0%
Common425
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
m384
13.5%
a329
11.6%
n327
11.5%
o321
11.3%
i213
7.5%
c180
 
6.3%
t172
 
6.0%
A141
 
5.0%
z141
 
5.0%
r109
 
3.8%
Other values (10)528
18.6%
Common
ValueCountFrequency (%)
.321
75.5%
,52
 
12.2%
52
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m384
11.7%
a329
10.1%
n327
10.0%
o321
9.8%
.321
9.8%
i213
 
6.5%
c180
 
5.5%
t172
 
5.3%
A141
 
4.3%
z141
 
4.3%
Other values (13)741
22.7%

Frequent disruption when moving from one page to another
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
53 
Myntra.com
52 
Snapdeal.com
49 
Paytm.com
39 
Flipkart.com
26 
Other values (3)
50 

Length

Max length26
Median length24
Mean length12.80669145
Min length9

Characters and Unicode

Total characters3445
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowMyntra.com
3rd rowPaytm.com
4th rowAmazon.in, Flipkart.com
5th rowSnapdeal.com

Common Values

ValueCountFrequency (%)
Amazon.in53
19.7%
Myntra.com52
19.3%
Snapdeal.com49
18.2%
Paytm.com39
14.5%
Flipkart.com26
9.7%
Amazon.in, Flipkart.com25
9.3%
Myntra.com, Snapdeal.com14
 
5.2%
Flipkart.com, Snapdeal.com11
 
4.1%

Length

2022-06-09T21:39:14.244561image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:14.344294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in78
24.5%
snapdeal.com74
23.2%
myntra.com66
20.7%
flipkart.com62
19.4%
paytm.com39
12.2%

Most occurring characters

ValueCountFrequency (%)
a393
11.4%
m358
 
10.4%
o319
 
9.3%
.319
 
9.3%
n296
 
8.6%
c241
 
7.0%
t167
 
4.8%
i140
 
4.1%
l136
 
3.9%
p136
 
3.9%
Other values (13)940
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2707
78.6%
Other Punctuation369
 
10.7%
Uppercase Letter319
 
9.3%
Space Separator50
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a393
14.5%
m358
13.2%
o319
11.8%
n296
10.9%
c241
8.9%
t167
6.2%
i140
 
5.2%
l136
 
5.0%
p136
 
5.0%
r128
 
4.7%
Other values (5)393
14.5%
Uppercase Letter
ValueCountFrequency (%)
A78
24.5%
S74
23.2%
M66
20.7%
F62
19.4%
P39
12.2%
Other Punctuation
ValueCountFrequency (%)
.319
86.4%
,50
 
13.6%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3026
87.8%
Common419
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a393
13.0%
m358
11.8%
o319
10.5%
n296
9.8%
c241
 
8.0%
t167
 
5.5%
i140
 
4.6%
l136
 
4.5%
p136
 
4.5%
r128
 
4.2%
Other values (10)712
23.5%
Common
ValueCountFrequency (%)
.319
76.1%
,50
 
11.9%
50
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a393
11.4%
m358
 
10.4%
o319
 
9.3%
.319
 
9.3%
n296
 
8.6%
c241
 
7.0%
t167
 
4.8%
i140
 
4.1%
l136
 
3.9%
p136
 
3.9%
Other values (13)940
27.3%

Website is as efficient as before
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
94 
Flipkart.com
47 
Amazon.in, Flipkart.com
45 
Amazon.in, Flipkart.com, Paytm.com
25 
Amazon.in, Paytm.com
18 
Other values (3)
40 

Length

Max length34
Median length24
Mean length15.82899628
Min length9

Characters and Unicode

Total characters4258
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowAmazon.in, Flipkart.com
3rd rowAmazon.in
4th rowAmazon.in, Flipkart.com, Paytm.com
5th rowPaytm.com

Common Values

ValueCountFrequency (%)
Amazon.in94
34.9%
Flipkart.com47
17.5%
Amazon.in, Flipkart.com45
16.7%
Amazon.in, Flipkart.com, Paytm.com25
 
9.3%
Amazon.in, Paytm.com18
 
6.7%
Paytm.com15
 
5.6%
Myntra.com, Snapdeal.com14
 
5.2%
Snapdeal.com11
 
4.1%

Length

2022-06-09T21:39:14.453003image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:14.550742image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in182
46.0%
flipkart.com117
29.5%
paytm.com58
 
14.6%
snapdeal.com25
 
6.3%
myntra.com14
 
3.5%

Most occurring characters

ValueCountFrequency (%)
m454
10.7%
a421
 
9.9%
n403
 
9.5%
o396
 
9.3%
.396
 
9.3%
i299
 
7.0%
c214
 
5.0%
t189
 
4.4%
A182
 
4.3%
z182
 
4.3%
Other values (13)1122
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3212
75.4%
Other Punctuation523
 
12.3%
Uppercase Letter396
 
9.3%
Space Separator127
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m454
14.1%
a421
13.1%
n403
12.5%
o396
12.3%
i299
9.3%
c214
6.7%
t189
5.9%
z182
5.7%
l142
 
4.4%
p142
 
4.4%
Other values (5)370
11.5%
Uppercase Letter
ValueCountFrequency (%)
A182
46.0%
F117
29.5%
P58
 
14.6%
S25
 
6.3%
M14
 
3.5%
Other Punctuation
ValueCountFrequency (%)
.396
75.7%
,127
 
24.3%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3608
84.7%
Common650
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
m454
12.6%
a421
11.7%
n403
11.2%
o396
11.0%
i299
8.3%
c214
 
5.9%
t189
 
5.2%
A182
 
5.0%
z182
 
5.0%
l142
 
3.9%
Other values (10)726
20.1%
Common
ValueCountFrequency (%)
.396
60.9%
,127
 
19.5%
127
 
19.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m454
10.7%
a421
 
9.9%
n403
 
9.5%
o396
 
9.3%
.396
 
9.3%
i299
 
7.0%
c214
 
5.0%
t189
 
4.4%
A182
 
4.3%
z182
 
4.3%
Other values (13)1122
26.4%
Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Amazon.in
79 
Amazon.in, Flipkart.com
62 
Flipkart.com
39 
Amazon.in, Myntra.com
30 
Amazon.in, Paytm.com, Myntra.com
20 
Other values (3)
39 

Length

Max length49
Median length35
Mean length19.32713755
Min length9

Characters and Unicode

Total characters5199
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlipkart.com
2nd rowAmazon.in, Myntra.com
3rd rowAmazon.in, Paytm.com, Myntra.com
4th rowAmazon.in, Flipkart.com
5th rowAmazon.in, Myntra.com

Common Values

ValueCountFrequency (%)
Amazon.in79
29.4%
Amazon.in, Flipkart.com62
23.0%
Flipkart.com39
14.5%
Amazon.in, Myntra.com30
 
11.2%
Amazon.in, Paytm.com, Myntra.com20
 
7.4%
Amazon.in, Flipkart.com, Myntra.com15
 
5.6%
Amazon.in, Paytm.com13
 
4.8%
Flipkart.com, Paytm.com, Myntra.com, snapdeal.com11
 
4.1%

Length

2022-06-09T21:39:14.663440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-09T21:39:14.765168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in219
45.9%
flipkart.com127
26.6%
myntra.com76
 
15.9%
paytm.com44
 
9.2%
snapdeal.com11
 
2.3%

Most occurring characters

ValueCountFrequency (%)
n525
 
10.1%
m521
 
10.0%
a488
 
9.4%
o477
 
9.2%
.477
 
9.2%
i346
 
6.7%
c258
 
5.0%
t247
 
4.8%
A219
 
4.2%
z219
 
4.2%
Other values (13)1422
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3840
73.9%
Other Punctuation685
 
13.2%
Uppercase Letter466
 
9.0%
Space Separator208
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n525
13.7%
m521
13.6%
a488
12.7%
o477
12.4%
i346
9.0%
c258
6.7%
t247
6.4%
z219
5.7%
r203
 
5.3%
l138
 
3.6%
Other values (6)418
10.9%
Uppercase Letter
ValueCountFrequency (%)
A219
47.0%
F127
27.3%
M76
 
16.3%
P44
 
9.4%
Other Punctuation
ValueCountFrequency (%)
.477
69.6%
,208
30.4%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4306
82.8%
Common893
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n525
12.2%
m521
12.1%
a488
11.3%
o477
11.1%
i346
8.0%
c258
 
6.0%
t247
 
5.7%
A219
 
5.1%
z219
 
5.1%
r203
 
4.7%
Other values (10)803
18.6%
Common
ValueCountFrequency (%)
.477
53.4%
,208
23.3%
208
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n525
 
10.1%
m521
 
10.0%
a488
 
9.4%
o477
 
9.2%
.477
 
9.2%
i346
 
6.7%
c258
 
5.0%
t247
 
4.8%
A219
 
4.2%
z219
 
4.2%
Other values (13)1422
27.4%

Interactions

2022-06-09T21:38:59.511777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-06-09T21:39:14.912773image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-06-09T21:39:15.757523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-06-09T21:39:16.881749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-06-09T21:39:17.764359image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-06-09T21:39:20.847289image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-06-09T21:38:59.925581image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

1Gender of respondent2 How old are you?3 Which city do you shop online from?4 What is the Pin Code of where you shop online from?5 Since How Long You are Shopping Online ?6 How many times you have made an online purchase in the past 1 year?7 How do you access the internet while shopping on-line?8 Which device do you use to access the online shopping?9 What is the screen size of your mobile device?10 What is the operating system (OS) of your device?11 What browser do you run on your device to access the website?12 Which channel did you follow to arrive at your favorite online store for the first time?13 After first visit, how do you reach the online retail store?14 How much time do you explore the e- retail store before making a purchase decision?15 What is your preferred payment Option?16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart?17 Why did you abandon the “Bag”, “Shopping Cart”?18 The content on the website must be easy to read and understand19 Information on similar product to the one highlighted is important for product comparison20 Complete information on listed seller and product being offered is important for purchase decision.21 All relevant information on listed products must be stated clearly22 Ease of navigation in website23 Loading and processing speed24 User friendly Interface of the website25 Convenient Payment methods26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time27 Empathy (readiness to assist with queries) towards the customers28 Being able to guarantee the privacy of the customer29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.)30 Online shopping gives monetary benefit and discounts31 Enjoyment is derived from shopping online32 Shopping online is convenient and flexible33 Return and replacement policy of the e-tailer is important for purchase decision34 Gaining access to loyalty programs is a benefit of shopping online35 Displaying quality Information on the website improves satisfaction of customers36 User derive satisfaction while shopping on a good quality website or application37 Net Benefit derived from shopping online can lead to users satisfaction38 User satisfaction cannot exist without trust39 Offering a wide variety of listed product in several category40 Provision of complete and relevant product information41 Monetary savings42 The Convenience of patronizing the online retailer43 Shopping on the website gives you the sense of adventure44 Shopping on your preferred e-tailer enhances your social status45 You feel gratification shopping on your favorite e-tailer46 Shopping on the website helps you fulfill certain roles47 Getting value for money spentFrom the following, tick any (or all) of the online retailers you have shopped from;Easy to use website or applicationVisual appealing web-page layoutWild variety of product on offerComplete, relevant description information of productsFast loading website speed of website and applicationReliability of the website or applicationQuickness to complete purchaseAvailability of several payment optionsSpeedy order deliveryPrivacy of customers’ informationSecurity of customer financial informationPerceived TrustworthinessPresence of online assistance through multi-channelLonger time to get logged in (promotion, sales period)Longer time in displaying graphics and photos (promotion, sales period)Late declaration of price (promotion, sales period)Longer page loading time (promotion, sales period)Limited mode of payment on most products (promotion, sales period)Longer delivery periodChange in website/Application designFrequent disruption when moving from one page to anotherWebsite is as efficient as beforeWhich of the Indian online retailer would you recommend to a friend?
003Delhi1100095443511113433433441222544312243545332344545Amazon.in, Paytm.comPaytm.comFlipkart.comFlipkart.comSnapdeal.comSnapdeal.comPaytm.comPaytm.comPatym.comAmazon.inAmazon.inAmazon.inFlipkart.comPaytm.comAmazon.inAmazon.inFlipkart.comFlipkart.comAmazon.inPaytm.comFlipkart.comAmazon.inAmazon.inFlipkart.com
112Delhi1100305521231145155555555555555555555555555333555Amazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Myntra.comFlipkart.com, Myntra.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Myntra.comMyntra.comAmazon.com, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.comMyntra.comMyntra.comMyntra.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.comMyntra.comsnapdeal.comSnapdeal.comSnapdeal.comSnapdeal.comAmazon.inMyntra.comAmazon.in, Flipkart.comAmazon.in, Myntra.com
212Greater Noida2013084531421144435544444555555555555554555444334Amazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.comAmazon.in, Paytm.com, Myntra.comAmazon.com, Paytm.com, Myntra.comPatym.com, Myntra.comAmazon.inAmazon.inAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comMyntra.comMyntra.comMyntra.comMyntra.comMyntra.comAmazon.inPaytm.comPaytm.comPaytm.comAmazon.inAmazon.in, Paytm.com, Myntra.com
302Karnal1320014131432113112443454554554433433434445445434Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.comAmazon.com, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealSnapdeal.comMyntra.com, Snapdeal.comMyntra.comPaytm.comPaytm.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com
412Bangalore5300683221232345142533445554545555524555445431515Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comMyntra.comMyntra.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Paytm.com, Myntra.comAmazon.com, Flipkart.com, Paytm.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Paytm.comPaytm.comAmazon.in, Myntra.comAmazon.in, Myntra.comFlipkart.com, Paytm.comPaytm.comPaytm.comPaytm.comSnapdeal.comPaytm.comAmazon.inSnapdeal.comPaytm.comAmazon.in, Myntra.com
513Noida2013085521421145442555555555555555555555555553345Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Paytm.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comPaytm.comAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.comFlipkart.com, Paytm.com, Snapdeal.comAmazon.in, Paytm.comAmazon.in, Paytm.comAmazon.in, Paytm.comAmazon.in, Paytm.comFlipkart.comPaytm.comFlipkart.comAmazon.inAmazon.in, Paytm.com
604Delhi1100115424521435135444444444444444554444434433444Amazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.inFlipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.com, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Snapdeal.comAmazon.inMyntra.comMyntra.comFlipkart.comSnapdeal.comMyntra.comMyntra.comSnapdeal.comFlipkart.com, Paytm.com, Myntra.com, snapdeal.com
704Delhi1100184133511123131122112122135115555541555551114Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.inAmazon.comAmazon.in, Flipkart.comAmazon.inPaytm.comFlipkart.comAmazon.inAmazon.inAmazon.in, Flipkart.comAmazon.in, Flipkart.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comFlipkart.comAmazon.inAmazon.inAmazon.inAmazon.in
811Solan1732293121421132234545444555555545445555544443343Amazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, SnapdealFlipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.inAmazon.in, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Snapdeal.comAmazon.inAmazon.inAmazon.inMyntra.com, Snapdeal.comMyntra.com, Snapdeal.comAmazon.in
913Delhi1100391122511115233454455545555444544454444443334Amazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.com, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comPaytm.comAmazon.in, Flipkart.comPaytm.comPaytm.comSnapdeal.comSnapdeal.comMyntra.comMyntra.comFlipkart.comFlipkart.com

Last rows

1Gender of respondent2 How old are you?3 Which city do you shop online from?4 What is the Pin Code of where you shop online from?5 Since How Long You are Shopping Online ?6 How many times you have made an online purchase in the past 1 year?7 How do you access the internet while shopping on-line?8 Which device do you use to access the online shopping?9 What is the screen size of your mobile device?10 What is the operating system (OS) of your device?11 What browser do you run on your device to access the website?12 Which channel did you follow to arrive at your favorite online store for the first time?13 After first visit, how do you reach the online retail store?14 How much time do you explore the e- retail store before making a purchase decision?15 What is your preferred payment Option?16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart?17 Why did you abandon the “Bag”, “Shopping Cart”?18 The content on the website must be easy to read and understand19 Information on similar product to the one highlighted is important for product comparison20 Complete information on listed seller and product being offered is important for purchase decision.21 All relevant information on listed products must be stated clearly22 Ease of navigation in website23 Loading and processing speed24 User friendly Interface of the website25 Convenient Payment methods26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time27 Empathy (readiness to assist with queries) towards the customers28 Being able to guarantee the privacy of the customer29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.)30 Online shopping gives monetary benefit and discounts31 Enjoyment is derived from shopping online32 Shopping online is convenient and flexible33 Return and replacement policy of the e-tailer is important for purchase decision34 Gaining access to loyalty programs is a benefit of shopping online35 Displaying quality Information on the website improves satisfaction of customers36 User derive satisfaction while shopping on a good quality website or application37 Net Benefit derived from shopping online can lead to users satisfaction38 User satisfaction cannot exist without trust39 Offering a wide variety of listed product in several category40 Provision of complete and relevant product information41 Monetary savings42 The Convenience of patronizing the online retailer43 Shopping on the website gives you the sense of adventure44 Shopping on your preferred e-tailer enhances your social status45 You feel gratification shopping on your favorite e-tailer46 Shopping on the website helps you fulfill certain roles47 Getting value for money spentFrom the following, tick any (or all) of the online retailers you have shopped from;Easy to use website or applicationVisual appealing web-page layoutWild variety of product on offerComplete, relevant description information of productsFast loading website speed of website and applicationReliability of the website or applicationQuickness to complete purchaseAvailability of several payment optionsSpeedy order deliveryPrivacy of customers’ informationSecurity of customer financial informationPerceived TrustworthinessPresence of online assistance through multi-channelLonger time to get logged in (promotion, sales period)Longer time in displaying graphics and photos (promotion, sales period)Late declaration of price (promotion, sales period)Longer page loading time (promotion, sales period)Limited mode of payment on most products (promotion, sales period)Longer delivery periodChange in website/Application designFrequent disruption when moving from one page to anotherWebsite is as efficient as beforeWhich of the Indian online retailer would you recommend to a friend?
25913Greater Noida2013105222511114132551555555551335535555454432245Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.com, Flipkart.comAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Snapdeal.comSnapdeal.comsnapdeal.comMyntra.comSnapdeal.comSnapdeal.comPaytm.comSnapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com
26013Noida2013085521421145442555555555555555555555555553345Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Paytm.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comPaytm.comAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.comFlipkart.com, Paytm.com, Snapdeal.comAmazon.in, Paytm.comAmazon.in, Paytm.comAmazon.in, Paytm.comAmazon.in, Paytm.comFlipkart.comPaytm.comFlipkart.comAmazon.inAmazon.in, Paytm.com
26112Greater Noida2013084531421144435544444555555555555554555444334Amazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.comAmazon.in, Paytm.com, Myntra.comAmazon.com, Paytm.com, Myntra.comPatym.com, Myntra.comAmazon.inAmazon.inAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comMyntra.comMyntra.comMyntra.comMyntra.comMyntra.comAmazon.inPaytm.comPaytm.comPaytm.comAmazon.inAmazon.in, Paytm.com, Myntra.com
26212Bangalore5600373221232345142533445554545555524555445431515Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comMyntra.comMyntra.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Paytm.com, Myntra.comAmazon.com, Flipkart.com, Paytm.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Paytm.comPaytm.comAmazon.in, Myntra.comAmazon.in, Myntra.comFlipkart.com, Paytm.comPaytm.comPaytm.comPaytm.comSnapdeal.comPaytm.comAmazon.inSnapdeal.comPaytm.comAmazon.in, Myntra.com
26304Delhi1100184133511123131122112122135115555541555551114Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.inAmazon.comAmazon.in, Flipkart.comAmazon.inPaytm.comFlipkart.comAmazon.inAmazon.inAmazon.in, Flipkart.comAmazon.in, Flipkart.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comFlipkart.comAmazon.inAmazon.inAmazon.inAmazon.in
26412Solan1732122131424415212444444444444333233234432324343Amazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.comAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.in
26513Ghaziabad2010082431521141231555555555555555555555555555555Amazon.in, Flipkart.comFlipkart.comAmazon.inAmazon.inFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.comFlipkart.com
26614Bangalore5600103132511115132554454454334434534444354423444Amazon.in, Flipkart.com, Snapdeal.comAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.comAmazon.in, Flipkart.comAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inSnapdeal.comAmazon.inSnapdeal.comSnapdeal.comSnapdeal.comSnapdeal.comSnapdeal.comAmazon.inAmazon.in
26711Solan1732293121421132234545444555555545445555544443343Amazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, SnapdealFlipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.inAmazon.in, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Snapdeal.comAmazon.inAmazon.inAmazon.inMyntra.com, Snapdeal.comMyntra.com, Snapdeal.comAmazon.in
26814Ghaziabad2010093431421144215555555555555555554555555555555Amazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.comAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.in

Duplicate rows

Most frequently occurring

1Gender of respondent2 How old are you?3 Which city do you shop online from?4 What is the Pin Code of where you shop online from?5 Since How Long You are Shopping Online ?6 How many times you have made an online purchase in the past 1 year?7 How do you access the internet while shopping on-line?8 Which device do you use to access the online shopping?9 What is the screen size of your mobile device?10 What is the operating system (OS) of your device?11 What browser do you run on your device to access the website?12 Which channel did you follow to arrive at your favorite online store for the first time?13 After first visit, how do you reach the online retail store?14 How much time do you explore the e- retail store before making a purchase decision?15 What is your preferred payment Option?16 How 4 do you abandon (selecting an items and leaving without making payment) your shopping cart?17 Why did you abandon the “Bag”, “Shopping Cart”?18 The content on the website must be easy to read and understand19 Information on similar product to the one highlighted is important for product comparison20 Complete information on listed seller and product being offered is important for purchase decision.21 All relevant information on listed products must be stated clearly22 Ease of navigation in website23 Loading and processing speed24 User friendly Interface of the website25 Convenient Payment methods26 Trust that the online retail store will fulfill its part of the transaction at the stipulated time27 Empathy (readiness to assist with queries) towards the customers28 Being able to guarantee the privacy of the customer29 Responsiveness, availability of several communication channels (email, online rep, twitter, phone etc.)30 Online shopping gives monetary benefit and discounts31 Enjoyment is derived from shopping online32 Shopping online is convenient and flexible33 Return and replacement policy of the e-tailer is important for purchase decision34 Gaining access to loyalty programs is a benefit of shopping online35 Displaying quality Information on the website improves satisfaction of customers36 User derive satisfaction while shopping on a good quality website or application37 Net Benefit derived from shopping online can lead to users satisfaction38 User satisfaction cannot exist without trust39 Offering a wide variety of listed product in several category40 Provision of complete and relevant product information41 Monetary savings42 The Convenience of patronizing the online retailer43 Shopping on the website gives you the sense of adventure44 Shopping on your preferred e-tailer enhances your social status45 You feel gratification shopping on your favorite e-tailer46 Shopping on the website helps you fulfill certain roles47 Getting value for money spentFrom the following, tick any (or all) of the online retailers you have shopped from;Easy to use website or applicationVisual appealing web-page layoutWild variety of product on offerComplete, relevant description information of productsFast loading website speed of website and applicationReliability of the website or applicationQuickness to complete purchaseAvailability of several payment optionsSpeedy order deliveryPrivacy of customers’ informationSecurity of customer financial informationPerceived TrustworthinessPresence of online assistance through multi-channelLonger time to get logged in (promotion, sales period)Longer time in displaying graphics and photos (promotion, sales period)Late declaration of price (promotion, sales period)Longer page loading time (promotion, sales period)Limited mode of payment on most products (promotion, sales period)Longer delivery periodChange in website/Application designFrequent disruption when moving from one page to anotherWebsite is as efficient as beforeWhich of the Indian online retailer would you recommend to a friend?# duplicates
2211Solan1732293121421132234545444555555545445555544443343Amazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, SnapdealFlipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.inAmazon.in, Myntra.com, Snapdeal.comAmazon.inAmazon.in, Snapdeal.comAmazon.inAmazon.inAmazon.inMyntra.com, Snapdeal.comMyntra.com, Snapdeal.comAmazon.in8
502Karnal1320014131432113112443454554554433433434445445434Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.comAmazon.com, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealSnapdeal.comMyntra.com, Snapdeal.comMyntra.comPaytm.comPaytm.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com7
3012Greater Noida2013084531421144435544444555555555555554555444334Amazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comAmazon.in, Paytm.com, Myntra.comAmazon.in, Paytm.comAmazon.in, Paytm.com, Myntra.comAmazon.com, Paytm.com, Myntra.comPatym.com, Myntra.comAmazon.inAmazon.inAmazon.in, Paytm.com, Myntra.comAmazon.in, Myntra.comMyntra.comMyntra.comMyntra.comMyntra.comMyntra.comAmazon.inPaytm.comPaytm.comPaytm.comAmazon.inAmazon.in, Paytm.com, Myntra.com7
4313Greater Noida2013105222511114132551555555551335535555454432245Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.com, Flipkart.comAmazon.in, Flipkart.com, Patym.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Snapdeal.comSnapdeal.comsnapdeal.comMyntra.comSnapdeal.comSnapdeal.comPaytm.comSnapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com7
5714Noida2013085122511135132554554544555325545554355324434Amazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.inAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.inAmazon.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Snapdeal.comAmazon.inAmazon.in, SnapdealPaytm.comFlipkart.com, Snapdeal.comMyntra.comMyntra.comSnapdeal.comMyntra.comPaytm.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com7
6015Gurgaon1220183122511135132555555555553444555555553423324Amazon.in, Flipkart.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, Snapdeal.comFlipkart.com, Myntra.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Myntra.comAmazon.in, Flipkart.comAmazon.com, Flipkart.com, Myntra.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Myntra.comAmazon.inAmazon.inAmazon.inAmazon.in, Flipkart.comMyntra.comSnapdeal.comsnapdeal.comPaytm.com, Snapdeal.comPaytm.com, Snapdeal.comPaytm.com, Snapdeal.comAmazon.in, Flipkart.comSnapdeal.comFlipkart.comAmazon.in, Flipkart.com, Myntra.com7
1003Moradabad2440015332511133131534545445454234513425342342243Amazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Paytm.comAmazon.in, Flipkart.com, Paytm.comAmazon.com, Flipkart.com, Paytm.comAmazon.in, Patym.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Paytm.comAmazon.inAmazon.in, Paytm.comAmazon.in, Flipkart.comFlipkart.comFlipkart.com, Snapdeal.comAmazon.in, Flipkart.comPaytm.com, Snapdeal.comAmazon.inFlipkart.com, Snapdeal.comAmazon.in, Paytm.comAmazon.in5
1504Delhi1100115424521435135444444444444444554444434433444Amazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.inFlipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.com, Flipkart.com, Paytm.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.com, Snapdeal.comAmazon.in, Flipkart.com, Myntra.com, SnapdealAmazon.in, Flipkart.com, Snapdeal.comAmazon.inMyntra.comMyntra.comFlipkart.comSnapdeal.comMyntra.comMyntra.comSnapdeal.comFlipkart.com, Paytm.com, Myntra.com, snapdeal.com5
1604Delhi1100184133511123131122112122135115555541555551114Amazon.in, Flipkart.com, Paytm.com, Myntra.com, Snapdeal.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comAmazon.in, Flipkart.com, Paytm.comAmazon.inAmazon.comAmazon.in, Flipkart.comAmazon.inPaytm.comFlipkart.comAmazon.inAmazon.inAmazon.in, Flipkart.comAmazon.in, Flipkart.comPaytm.comAmazon.in, Flipkart.comAmazon.in, Flipkart.comFlipkart.comAmazon.inAmazon.inAmazon.inAmazon.in5
3512Solan1732122131424415212444444444444333233234432324343Amazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.comAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.inAmazon.in5